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Controlling wastewater pollution from centralized industrial zones is important for reducing overall water pollution. Microbial community structure and diversity can adversely affect wastewater treatment plant (WWTP) performance and stability. Therefore, we studied microbial structure, diversity, and metabolic functions in WWTPs that treat industrial or municipal wastewater. Sludge microbial community diversity and richness were the lowest for the industrial WWTPs, indicating that industrial influents inhibited bacterial growth. The sludge of industrial WWTP had low Nitrospira populations, indicating that influent composition affected nitrification and denitrification. The sludge of industrial WWTPs had high metabolic functions associated with xenobiotic and amino acid metabolism. Furthermore, bacterial richness was positively correlated with conventional pollutants (e.g., carbon, nitrogen, and phosphorus), but negatively correlated with total dissolved solids. This study was expected to provide a more comprehensive understanding of activated sludge microbial communities in full-scale industrial and municipal WWTPs.

Anaerobic digestion (AD) has been used widely as a form of energy recovery by biogas production from the organic fraction of municipal solid wastes (OFMSW). The aim of this study was to evaluate the effect of the introduction of co-substrates (restaurant wastes, corn whole stillage, effluents from the cleaning of chocolate transportation tanks) on the thermophilic anaerobic digestion process of the mechanically separated organic fraction of municipal solid wastes in a full-scale mechanical-biological treatment (MBT) plant. Based on the results, it can be seen that co-digestion might bring benefits and process efficiency improvement, compared to mono-substrate digestion. The 15% addition of effluents from the cleaning of chocolate transportation tanks resulted in an increase in biogas yield by 31.6%, followed by a 68.5 kWh electricity production possibility. The introduction of 10% corn stillage as the feedstock resulted in a biogas yield increase by 27.0%. The 5% addition of restaurant wastes contributed to a biogas yield increase by 21.8%. The introduction of additional raw materials, in fixed proportions in relation to the basic substrate, increases biogas yield compared to substrates with a lower content of organic matter. In regard to substrates with high organic loads, such as restaurant waste, it allows them to be digested. Therefore, determining the proportion of different feedstocks to achieve the highest efficiency with stability is necessary.

Effective assessment of biodiversity in cities requires detailed vegetation maps. To date, most remote sensing of urban vegetation has focused on thematically coarse land cover products. Detailed habitat maps are created by manual interpretation of aerial photographs, but this is time consuming and costly at large scale. To address this issue, we tested the effectiveness of object-based classifications that use automated image segmentation to extract meaningful ground features from imagery. We applied these techniques to very high resolution multispectral Ikonos images to produce vegetation community maps in Dunedin City, New Zealand. An Ikonos image was orthorectified and a multi-scale segmentation algorithm used to produce a hierarchical network of image objects. The upper level included four coarse strata: industrial/commercial (commercial buildings), residential (houses and backyard private gardens), vegetation (vegetation patches larger than 0.8/1ha), and water. We focused on the vegetation stratum that was segmented at more detailed level to extract and classify fifteen classes of vegetation communities. The first classification yielded a moderate overall classification accuracy (64%, κ = 0.52), which led us to consider a simplified classification with ten vegetation classes. The overall classification accuracy from the simplified classification was 77% with a κ value close to the excellent range (κ = 0.74). These results compared favourably with similar studies in other environments. We conclude that this approach does not provide maps as detailed as those produced by manually interpreting aerial photographs, but it can still extract ecologically significant classes. It is an efficient way to generate accurate and detailed maps in significantly shorter time. The final map accuracy could be improved by integrating segmentation, automated and manual classification in the mapping process, especially when considering important vegetation classes with limited spectral contrast.

This review paper considers the disjuncture between the rapid pace of climate change and the more sluggish ability of cities to fully implement effective strategies of climate change adaptation and mitigation. We will refer to this as the ‘slow city–quick climate change’ dilemma. Climate change is accelerating, quickly rendering obsolete previous urban forms inadequate, while structural adjustments to cities are slower moving. Cities around the world were largely built for previous climate regimes. In the short to medium term, there is a mismatch between the climate regime that cities were designed for and the climate regime they now inhabit. The paper is divided into four parts: a brief review of climate change in general; climate change in cities; a review of climate change adaptation and mitigation in cities; and finally, a discussion of urban futures in the time of climate regime change.

Environmental pollution is a problem of universal concern throughout the globe. The development of real estate industry not only consumes huge resources, but also has close ties with high-consumption industries such as the construction industry. However, previous studies have rarely explored the impact of real estate development on environmental pollution. Therefore, this paper employs the entropy method to construct a comprehensive index of environmental pollution based on panel data of 31 provinces in China from 2000 to 2017, and empirically examines the impact of real estate development on environmental pollution. This article uses real estate investment to measure the development of the real estate industry. In view of the high spatial autocorrelation of environmental pollution, this paper selects a spatial econometric model. The empirical study found that: (1) By using the Spatial Durbin Model, real estate development has an inverted U-shaped impact on environmental pollution. Meanwhile, most cities have not yet reached the turning point; that is, with the continuous development of the real estate industry, environmental pollution will continue to increase. (2) Further regional heterogeneity found that the inverted U-shaped relationship still exists in coastal and inland areas. (3) Finally, this article used the Spatial Mediation Model to explain the nonlinear impact of real estate development on environmental pollution, with two important mediating variables: population density and industrial structure. Through the above analysis, it can be observed that real estate development has a significant impact on environmental pollution. Thus, the country and the government can reduce environmental pollution by improving the investment structure, using environmentally friendly building materials, guiding population flow and promoting industrial upgrading.

The evaluation index system of urban aquatic ecosystem health is of great significance for the assessment and management of urban river networks, and for urban development planning. In this paper, the concept of urban aquatic ecosystem health was analyzed by the relationship between human, city and aquatic ecosystem, and its evaluation index system was established from environmental conditions, ecological construction, and social service. In addition, the weight value of each index was calculated by the analytic hierarchy process, and the grading standard of each index was set. Jiading New City, a typical city of the river network plain area in Yangtze River delta, was selected as the aquatic ecosystem health evaluation sample. The fuzzy comprehensive method was used to evaluate the aquatic ecosystem health of Jiading New City. The results indicated that the water ecosystem health of Jiading New City reached the “good” level. For the criterion level, environmental conditions and ecological construction reached the “good” level, and social services reached the “excellent” level. For the indicator level, most indicators reached “good” and “excellent” levels, but the river complexity and benthic macroinvertebrate diversity are still in the “poor” state, which indicates that the aquatic environment has greatly improved, but the aquatic ecosystem has not been fully restored. Results suggested that river complexity and biodiversity should be increased in urban construction planning. The evaluation index system established in this paper can be used to reflect the urban aquatic ecosystem health conditions in river network plain areas.

Based on the data from 35 major cities in China in 2020, this paper applies the Simpson’s diversity index, the entropy value method, and the coupling coordination degree model to comprehensively measure the coupling coordination level of mixed land use and urban vitality in major cities in China and further analyze their spatial distribution characteristics. In addition, this paper analyzes the factors affecting the spatial variation of the coupling coordination level with the help of the geographic probe model. The study finds that: (1) The overall level of coupling coordination between mixed land use and urban vitality is high in 35 major cities in China. There is no disorder between mixed land use and urban vitality. (2) In terms of the spatial distribution of the coupling coordination between mixed land use and urban vitality in 35 cities in China, five cities, namely Beijing, Shenzhen, Shanghai, Guangzhou, and Chengdu, have the highest level of coupling coordination between mixed land use and urban vitality, reaching “good coordination” with a discrete spatial distribution. Central cities such as Hangzhou and Nanjing have the second highest level of coupling coordination and are at the “intermediate coordinate” with a “strip-like distribution” in space. Twenty cities in the north and south have the lowest coupling coordination levels and are in the “primary coordination.” Among these twenty cities, seven cities in the south have a higher level of coupling coordination than thirteen cities in the north, with a spatial distribution of a “C” shape. The northern cities have the lowest level of coupling coordination, with a “W”-shaped distribution in space. (3) Population size plays an essential role in guiding the level of coupling coordination between mixed land use and urban vitality in major cities in China, followed by government regulation and economic level. At the same time, transportation conditions and industrial structure have the weakest influence on the level of coupling coordination between mixed land use and urban vitality in major cities in China.

In the realistic context of the development of China’s digital economy and carbon peaking and carbon neutrality goals, to efficiently achieve high-quality economic and green and low-carbon transformation, this paper investigates the impact of digital economy development on the carbon emission efficiency of 30 Chinese provinces and cities from 2011–2019. In this paper, firstly, the digital economy development index and carbon emission efficiency are calculated by the entropy method and the Super-SBM-Undesirable Model. Secondly, the Spatial Lag Model (SAR) and the Spatial Durbin Model (SDM) are respectively constructed under the adjacency matrix and the geographic distance matrix to empirically test the spatial impact of the digital economy on carbon emission efficiency. The results show that: the digital economy development and carbon emission efficiency of Chinese provinces and cities both show the spatial distribution characteristics of stronger in the East and weaker in the Middle and West; the digital economy development in Chinese provinces and cities has a significantly positive direct and spatial spillover effect on carbon emission efficiency; there are differences in the direct and spatial spillover effects of various dimensions of the digital economy development on the carbon emission efficiency in Chinese provinces and cities; the direct effect of the digital economy development on the carbon emission efficiency in Chinese provinces and cities has significant regional heterogeneity among eastern, central, and western regions. This paper provides new empirical evidence for developing countries such as China to proactively develop a digital economy to promote energy conservation and emission reduction to realize green and low-carbon transformation.

The degradation of rivers in urban landscapes is alarming and impaired their ecological functions and the services they provide to society. In African cities, urban rivers are among the most degraded ecosystems, yet ecologically sustainable utilisation of river resources can contribute to and support sustainable urban development. In this paper, we identify and analyse key governance and institutional drivers of ecological change in urban river systems in the Swartkops catchment in South Africa and the Federal Capital Territory (FCT) in Nigeria. Our results indicate that poor ecological conditions of rivers in the two urban landscapes can be attributed to: (1) a lack of system view of the water value chain and associated infrastructure, (2) ambiguity in roles, responsibilities, and poor accountability, (3) prioritizing short-term social–economic–political agenda over long-term environmental sustainability goals, (4) institutional silos and failure of cooperative governance, and (5) over-centralised, top-down, state-centric governance processes. Strengthening the interactions between actors in the science, policy and practice domains, mainstreaming planning with rivers in integrated urban development plans, and strengthening cooperative and polycentric governance across administrative scales are key governance and institutional processes needed to address the trajectory of urban ecological degradation. Our paper sheds light on the fundamental role of strengthening governance and institutional processes for steering urban rivers toward sustainable paths for city resilience.

Can environmental regulation promote green innovation and the productivity of cities? The “Compliance Cost” (CC) perspective and the “Porter Hypothesis” (PH) offer contrasting views, whereas the existing empirical results are inconclusive. This paper aims to highlight the roles of multifaceted government interventions, including government-to-firm subsidies, tax levies on firms, and environmental infrastructure provisions, in moderating environmental regulation for realizing PH. Based on the fixed-effects models for Chinese prefecture cities from 2005–2013, we found that environmental regulation positively impacted green innovation but negatively affected productivity. The results of moderating effects suggest that environmental regulation can better promote green innovation if it is compounded with more government-to-firm subsidies, lower firm tax burdens, and increased environmental infrastructure provisions. We further decomposed the impacts of these interventions across seven fields of green innovation and found that subsidy and tax burden relief were especially effective in facilitating more GI in the sector of transportation and alternative energy production. This paper amplifies the theoretical framework of PH by accentuating the analytical lens of multifaceted government interventions but also provides insights into how local governments can effectively design “carrot-and-stick” policies to realize PH at the city level.

In the context of rapid urbanization and limited land amount, it is essential to scientifically evaluate the urban land green use efficiency (ULGUE) to promote regional sustainable development. Current studies are of great value for enriching the theoretical system and application research of ULGUE. Still, most of them only consider industrial pollution but ignore carbon emission as an essential environmental influencing indicator. This paper introduced carbon emissions into the input-output indicator system, measured ULGUE of 57 cities in the Yellow River Basin (YRB) over the 2004–2017 periods using the super-efficiency slacked-based measure (Super-SBM) model, analyzed its spatio-temporal patterns with the kernel density estimation (KDE) model and spatial autocorrelation model, and then identified the influencing factors with the Spatial Durbin model (SDM). As shown by the results, firstly, the ULGUE in the YRB over the 2004–2017 periods showed a trend of first decreasing and then increasing. Secondly, the ULGUE exhibited spatio-temporal imbalance characteristics across the YRB. Thirdly, ULGUE was the interaction of multiple indicators, and its influencing factors had spatial spillover effects. All in all, this paper is fundamental to the high-quality development of cities in the background of the Chinese policy of “carbon peak, carbon neutralization”.

In the context of the coronavirus disease 2019 (COVID-19), people’s social mentality and mental health have been severely affected, which has hindered or even reversed the achievement of the United Nations Sustainable Development Goals (SDGs). However, there is a lack of investigation into the potential relationship between social mentality and health, as well as of the comparison between different databases worldwide and in China, in the current context of COVID-19. Hence, the aim of this paper is to explore the research hotspots and development trends of social mentality and health in China and worldwide, while improving people’s health, building a sustainable society, and facilitating the achieving of the SDGs. A bibliometric method is employed in this paper from a macro-quantitative and micro-qualitative perspective to explore the research hotspots and trends of social mentality and health in the world and China from the two databases, namely the English-language Web of Science (WOS) and the Chinese-language China National Knowledge Infrastructure (CNKI). The results indicate that: (1) By using keyword co-occurrence and clustering analysis via the CiteSpace software bibliometric tool, 11 current research hotspots have been identified and studies are increasing in terms of using the Chinese language and the English language. (2) The current studies in the CNKI database mainly focus on the macro social environmental factors affecting social mentality and population research, while the studies in the WOS database pay more attention to social mentality and health in the context of the COVID-19 epidemic situation and a variety of professions. Hence, future research could explore the influencing factors and cultivation methods toward a healthy social mentality from the perspective of methodology and toward achieving SDG 3, providing healthy lives and promote well-being for all at all ages, and SDG 11, building sustainable cities and communities in the post-pandemic COVID-19 era.

This paper applied landscape indexes to evaluate the size, form, and structure of green spaces in the mountainous city of Chongqing and found that green spaces benefit from certain advantages in size, but the network suffered from low heterogeneity and limited interconnectivity. To ensure the integrity and continuity of ecological processes and improve the efficiency of ecosystem services (ES), the authors used Geographic Information System (GIS) software to conduct adaptability evaluation and adjacent buffer analysis for the existing green spaces, wetlands, rivers, and other landscapes with relatively high capacity for ES. We designed a comprehensive map of potential areas for UGS expansion by superimposing the maps obtained from adaptability evaluation and buffer analysis. We also proposed some strategies that respect, consider, and evaluate aspects and special features of urban environment to optimize green space planning and improve ES efficiency, such as protection of important areas, development of green corridors, and careful consideration of ecological processes and complex functions in urban areas. Based on these strategies, the paper put forth suggestions for green space planning to improve ES efficiency that can function as foundation for subsequent green space planning.

Citizens play a core role in sustainable cities as users of the services delivered by cities and as active participants in initiatives aimed at making cities more sustainable. This paper considers the role of citizens as information providers and discusses the conditions under which citizens can participate in the development of sustainable cities. The objective of this study is to document the sustainability of an urban transit system and evaluate its compliance, with citizen participation as a major contributor. The methodology used is intensive field visits, interviews, and a mixed analysis of Sant Andreu de Palomar District in Barcelona city. The circulating vehicles are quantitatively monitored, qualitative problems are detected, and the typology of vehicles and other aspects identified and detailed in the study are indicated. All this information is contrasted with that of the technological sensors in the sectors. The results indicate that vehicles in the current pattern of urban density planned under incorrect sensor operation influence sustainable behavior through agglomerative clustering. This paper provides recommendations for future urban sustainability assessment research, including the employment of mixed-methods research, among other strategies. This article is intended to assist policymakers and traffic engineers in evaluating the sustainability of urban transportation infrastructure projects considering citizens as sensors.

China and other emerging market countries have suffered from the problem of environmental pollution while developing rapidly in the past few decades. In recent years, many countries have introduced strict environmental regulations in order to achieve sustainable development. This paper discusses the relationship between environmental regulations and corporate green innovation from the perspective of regional leaders’ promotion pressure. The empirical results show that direct policy regulation within the region stimulates green innovation on the part of enterprises, and the promotion pressure of city leaders has a further positive moderating effect on the positive correlation between environmental regulations and enterprises’ green innovation. The conclusion of the study proves that a strict environmental policy can promote the effectiveness of an environmental performance appraisal system in the sustainable development plans of cities and enterprises. This paper not only reveals the influence path of official promotion pressure on the sustainable development of enterprises in the administrative area from the micro perspective but also sheds some light that may improve government governance and promote the transformation of enterprises.

For the last decade the Smart City concept has been under development, fostered by the growing urbanization of the world’s population and the need to handle the challenges that such a scenario raises. During this time many Smart City projects have been executed–some as proof-of-concept, but a growing number resulting in permanent, production-level deployments, improving the operation of the city and the quality of life of its citizens. Thus, Smart Cities are still a highly relevant paradigm which needs further development before it reaches its full potential and provides robust and resilient solutions. In this paper, the focus is set on the Internet of Things (IoT) as an enabling technology for the Smart City. In this sense, the paper reviews the current landscape of IoT-enabled Smart Cities, surveying relevant experiences and city initiatives that have embedded IoT within their city services and how they have generated an impact. The paper discusses the key technologies that have been developed and how they are contributing to the realization of the Smart City. Moreover, it presents some challenges that remain open ahead of us and which are the initiatives and technologies that are under development to tackle them. This research was partially funded by Spain State Research Agency (AEI) by means of the project FIERCE: Future Internet Enabled Resilient CitiEs (RTI2018-093475-A-I00). Prof. Song was supported by Smart City R&D project of the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (MOLIT), Ministry of Science and ICT (MSIT) (Grant 18NSPS-B149386-01).

Addressing the recent trend of the massive demand for resources and ubiquitous use for all citizens has led to the conceptualization of technologies such as the Internet of Things (IoT) and smart cities. Ubiquitous IoT connectivity can be achieved to serve both urban and underserved remote areas such as rural communities by deploying 5G mobile networks with Low Power Wide Area Network (LPWAN). The current architectures will not offer flexible connectivity to many IoT applications due to high service demand, data exchange, emerging technologies, and security challenges. Hence, this paper explores various architectures that consider a hybrid 5G-LPWAN-IoT and Smart Cities. This includes security challenges as well as endogenous security and solutions in 5G and LPWAN-IoT. The slicing of virtual networks using software-defined network (SDN)/network function virtualization (NFV) based on the different quality of service (QoS) to satisfy different services and quality of experience (QoE) is presented. Also, a strategy that considers the implementation of 5G jointly with Weightless-N (TVWS) technologies to reduce the cell edge interference is considered. Discussions on the need for ubiquity connectivity leveraging 5G and LPWAN-IoT are presented. In addition, future research directions are presented, including a unified 5G network and LPWAN-IoT architecture that will holistically support integration with emerging technologies and endogenous security for improved/secured smart cities and remote areas IoT applications. Finally, the use of LPWAN jointly with low earth orbit (LEO) satellites for ubiquitous IoT connectivity is advocated in this paper.

The tourism, urbanization, technology, and the ecological environment both promote and restrict each other. Coordinating the relationship between the four is of great significance to the realization of high-quality sustainable regional development. Taking the Yunnan–Guizhou–Sichuan region as an example, this paper constructs an uncoordinated coupling model for the tourism–urbanization–technology–ecological environment system. Using exploratory spatial analysis and geographic information systems, this paper reveals the temporal and spatial evolution law affecting the uncoordinated coupling relationship between tourism, urbanization, technology and the ecological environment in the Yunnan–Guizhou–Sichuan region from 2010 to 2020, before establishing a panel Tobit model that is used to explore the factors affecting the four systems. The research shows the following: (1) The level of comprehensive development for tourism, urbanization, technology, and the ecological environment in Yunnan, Guizhou, and Sichuan has increased rapidly. Of all these, the tourism industry was the most affected by COVID-19 in 2020, while the level of urbanization, technology, and ecological environment developments in the three provinces has become similar over time. (2) Uncoordinated development between cities is a prominent problem; while the uncoordinated coupling spatial agglomeration in various regions is relatively stable, the proportion of cities with no significant agglomeration form amounts to more than 70%, with mostly low–low (L–L) and high–high (H–H) agglomeration types. (3) The degree to which uncoordinated coupling exists among the four systems in the Yunnan–Guizhou–Sichuan region is affected by many factors. Only eco-environmental pressure has a significant positive correlation with the degree of uncoordinated coupling, while the tourism scale, economic urbanization, eco-environmental response, and investment in technology have a significant negative correlation. These results provide a theoretical basis and practical references for strengthening the government’s macro-control and promoting collaborative regional development.

Since the 20th century, a rapid process of motorization has begun. The main goal of researchers, engineers and technology companies is to increase the safety and optimality of the movement of vehicles, as well as to reduce the environmental damage caused by the automotive industry. The difficulty of managing traffic flows is that cars are driven by a person and their behavior, even in similar situations, is different and difficult to predict. To solve this problem, ground-based unmanned vehicles are increasingly being developed and implemented; however, like any other intelligent system, it is necessary to train different road scenarios. Currently, an engineer is driving an unmanned vehicle for training and thousands of kilometers are being driven for training. Of course, this approach to training unmanned vehicles is very long, and it is impossible to reproduce all the scenarios that can be found in real operations on a real road. Based on this, we offer a simulator of a realistic urban environment which allows you to reduce the training time and allows you to generate all kinds of events. To implement such a simulator, it is necessary to develop a method that would allow recreating a realistic world in one passage with cameras (monocular) installed on board the vehicle. Based on this, the purpose of this work is to develop an intelligent vehicle recognition system using convolutional neural networks, which allows you to create mesh objects for further placement in the simulator. It is important to note that the resulting objects should be optimal in size so as not to overload the system, since a large number of road infrastructure objects are stored there. Also, neural complexity should not be excessive. In this paper, the general concept and classification of convolutional neural networks are given, which allow solving the problem of recognizing 3D objects in images. Based on the analysis, the existing neural network architectures do not solve the problems mentioned above. In this connection, the authors first of all carried out the design of the system according to the methodology of modeling business processes, and also modified and developed the architecture of the neural network, which allows classifying objects with sufficient accuracy, obtaining optimized mesh objects and reducing computational complexity. The methods proposed in this paper are used in a simulator of a realistic urban environment, which reduces the time and computational costs when training unmanned transport systems.

Travel costs are critical to the sustainable development of cities. This paper used Urban Household Survey (UHS) data from 2002 to 2014 and constructed a comprehensive city-size index from the perspectives of population and urban space to empirically test the impact of city size on the cost of household travel. The main results are as follows: (1) There is a significant positive correlation between city size and the cost of household travel. The internal mechanism is that city size affects the cost of household travel by increasing spatial distance and traffic congestion. (2) Increasing public transportation and per capita road area can restrain the positive impact of city size on the cost of household travel; moreover, the restraining effect of public transportation is stronger than that of per capita road area. (3) The impact of city size on the cost of household travel for sub-provincial cities is smaller than that for ordinary prefecture-level cities; in addition, there is an inverted U-shaped relationship between city size and the cost of household travel. This paper deepens the understanding of the impact of city size on travel costs, providing research support for the healthy development of cities in China.

A research team collected 3609 useful soil samples across the city of Syracuse, NY, this data collection fieldwork occurred during the two consecutive summers (mid-May to mid-August) of 2003 and 2004. Each soil sample had fifteen heavy metals (As, Cr, Cu, Co, Fe, Hg, Mo, Mn, Ni, Pb, Rb, Se, Sr, Zn, and Zr), measured during its assaying, errors for these measurements are analyzed in this paper, with an objective of contributing to the geography of error literature. Geochemistry measurements are in milligrams of heavy metal per kilogram of soil, or ppm, together with accompanying analytical measurement errors. The purpose of this paper is to summarize and portray the geographic distribution of these selected heavy metals measurement errors across the city of Syracuse. Doing so both illustrates the value of the SAAR software’s uncertainty mapping module and uncovers heavy metal characteristics in the geographic distribution of Syracuse’s soil. In addition to uncertainty visualization portraying and indicating reliability information about heavy metal levels and their geographic patterns, SAAR also provides optimized map classifications of heavy metal levels based upon their uncertainty (utilizing the Sun-Wong separability criterion) as well as an optimality criterion that simultaneously accounts for heavy metal levels and their affiliated uncertainty. One major outcome is a summary and portrayal of the geographic distribution of As, Cr, Cu, Co, Fe, Hg, Mo, Mn, Ni, Pb, Rb, Se, Sr, Zn, and Zr measurement error across the city of Syracuse.

Tradable water volumes is one of the basic elements of water-rights trading. In China, water-rights transactions mostly occur in water-deficient areas. However, the water-rich areas are also facing serious water-shortage problems. It is necessary to stimulate the water-rights trading power in abundant water areas to improve water-resource predicament. This paper studied the concept and calculation method of tradable water volumes of industry. First, based on the property rights theory, we analyzed the concept of tradable water volumes, and put forward the preliminary determination of water-rights trading subjects. Then, we defined the tradable water volumes of industry as the difference between the initial water-rights allocation and the water demand of industry. We used the proportion method to calculate the initial water-rights allocation of industry under different runoff frequencies, and grey model (1,1) to predict the water demand of industry. Finally, we applied the calculation method to Changsha city which is in a water-rich area of China. The calculation results contribute to water-resource management in Changsha city. This paper will provide a theoretical basis for researching the tradable water volumes, and promote the development of water-rights trading in China&rsquo, s water-rich areas.

The emergence and development of car-sharing has not only satisfied people&rsquo, s diverse travel needs, but also brought new solutions for improving urban traffic conditions and achieving low-carbon and green sustainable development. In recent years, car-sharing has had competition with other ways of getting around, as the acceptance of car-sharing has grown, notably taxis. Therefore, it is particularly important to explore car-sharing travel costs advantages from the perspective of consumers and discover the competitive and complementary spaces between car-sharing and other modes. Therefore, taking Beijing as an example, this paper uses GPS trajectory data based on car-sharing orders to design a travel cost framework of car-sharing and taxis. We calculate and compare the travel cost difference between these two modes under different travel characteristics. The results indicate that car-sharing is a more economical way for consumers to travel for short or medium lengths of time, while people are more inclined to take taxis for distances of long duration. Compared with on workdays, at the weekend, the cost advantage of car-sharing is greater for long-distance trips. Moreover, the cost advantage of car-sharing increases gradually with the increase in travel distance. In addition, the travel costs of car-sharing and taxis are also affected by peak and off-peak traffic periods. Compared with off-peak periods, it is more cost-effective for travelers to take taxis during peak traffic periods for various travel distances. From the perspective of the travel cost, it is of great theoretical significance to discuss the substitution (market competition) and complementary relationship (market cooperation) between car-sharing and taxis in a detailed and systematic way. It provides methods and ideas for the comparative cost calculation of car-sharing and other travel modes. This paper also provides enlightenment and guidance for the development of car-sharing. Enterprises should implement differentiated pricing, designing different charging methods for different traffic periods, travel miles, and rental times, and set up additional stations in the surrounding areas of the city. Relevant government departments should also strictly manage the market access of car-sharing, and add or open car-sharing parking lots in centralized areas and for specific periods.

Based on a literature review and theoretical mechanism, this paper takes the implementation point of the adjustment and transformation policy for old industrial cities as the breakthrough point, and uses a regression model to explore the impact of the adjustment and transformation policy of these old industrial cities on urban carbon emissions. This paper also robustly tests the effective mechanisms and environmental hypotheses. Overall, the implementation of the adjustment and renovation policy has significantly reduced the carbon emissions of old industrial cities by about 0.068 units. Compared with the control group cities, the pilot cities reduced carbon emissions by an average of about 310,000 tons after the implementation of the policy. Based on a summary of the excellent Chinese case experience and an empirical analysis, it can be concluded that improvements in the green innovation capacity of old industrial cities, the agglomeration of high-end service industries, and the strengthening of ecological restoration are important mechanisms that lead to reduced carbon emissions. There is no subsequent exacerbation of the carbon intensity of neighboring cities, and there is insufficient evidence to prove pollution via neighboring transfers and use of the beggar-thy-neighbor policy. The extended analysis shows that the “inverted U-shaped” CO2 Kuznets environmental curve hypothesis is significantly present in the sample of old industrial cities, but most cities do not cross the threshold. In 2013, about 60% of the urban sample economic growth and carbon emissions showed signs of tapping into potentials and increasing efficiency (absolute decoupling) and intensive expansion (relative decoupling). In old industrial cities, the proportion of relative decoupling shows a fluctuating upward trend. In the future, the government should accurately select its own development orientation and actively seek the “best balance” between economic growth and a green and low-carbon path.

Traditional settlements have received increasing attention because of China’s rural revitalization. Traditional settlements with excellent thermal comfort in rural areas can attract urban residents, so it is vital to explore the thermal comfort of traditional settlements. For this paper, we studied Linpan settlements, which are scattered traditional settlements that are mainly composed of buildings and trees. Firstly, we visually interpreted Linpan settlements by ArcGIS. A total of 1194 Linpan settlements were classified to obtain the spatial components. The statistical results of Linpan were used in the subsequent experimental design. Then ENVI-met was used to simulate 25 different spatial forms of Linpan obtained by statistical results and orthogonal experiment to explore the most comfortable Linpan layout. The results showed the following: (1) Linpan could improve thermal comfort in both winter and summer. Adjusting the spatial arrangement could maximally increase the mean physiological equivalent temperature (PET) of the whole Linpan area by 1.03 °C in winter and reduce it by 3.02 °C in the summer. (2) At different time points, the influence of different space factors on thermal comfort was also different. The overall significance of each factor on thermal comfort was addressed as follows: vegetation coverage (highly significant) > building number (highly significant) > building form (highly significant) > vegetation distribution (significant), but the building distribution was not significant. (3) The best spatial arrangement scheme was high vegetation coverage, a large number of buildings, tri-courtyard buildings, surrounding vegetation distribution, and surrounding building distribution. The innovation of this paper lies in introduced thermal comfort into the traditional Linpan settlement, extracted spatial features of buildings and vegetation by visual interpretation combined with GIS software, and the fact that we conducted the experimental design of microclimate and thermal comfort based on spatial features. The research results can guide the outdoor thermal environment renewal design of Linpan and other traditional settlements.

The spatial layout of the “Production–Living–Ecological” (PLE) function and the spatial optimization of the “Urban–Agricultural–Ecological” (UAE) pattern are the key points and difficulties in territorial space planning. This paper analyzes their spatial concepts and holds that PLE space is a functional space, while UAE space belongs to a regional space. The optimization of the UAE pattern should be guided by the improvement of the PLE function. Therefore, taking Hefei City, China, as an example, this paper analyzes the evolution of the present UAE pattern, evaluates the PLE function under carbon constraint and then determines the improvement direction of the PLE function and finally simulates the future UAE pattern of territory space. The conclusions are as follows: ① From 2011 to 2019, the urban space increased incrementally, while the agricultural space and ecological space decreased continuously, and the urban space expansion squeezed the agricultural and ecological spaces greatly; ② The PLE functions of four districts in the main city are higher than that of five other counties. After the carbon constraint conditions are included, the PLE functions of the main city were reduced due to the relatively strong capacity of carbon source, while the counties’ increased due to a stronger carbon sink capacity; ③ According to the normalized revealed comparative advantage (NRCA) index, it was determined that the functional improvement direction of each district and county are Yaohai District and Shushan District have comprehensive function as a priority, Luyang District and Baohe District give priority to living–ecological function, Changfeng County, Feidong County, Feixi County and Chaohu County give priority to production–ecological function, and Lujiang County gives priority to ecological function; ④ The simulation results show that 2025 is an important node for the evolution of the UAE pattern. The urban spatial expansion during the “14th Five-Year Plan” period will still bring great pressure on agriculture and ecological spaces, and then, the UAE pattern will continue to be optimized and balanced.

Although tourism has increasingly become an important activity with wide influences on the economic, social, and spatial development of a city, knowledge and interest mostly remain on its industrial performance and promotion. The synergy between tourism and city development is largely overlooked in many cases, resulting in suboptimal design and planning of city tourism activities and unfledged potentials of city development. The aim of the paper is to propose a view of tourism–industrial complex based on a synergistic perspective in order to clarify the systematic characteristics of urban tourism in an integrated, sustainable manner. Availing of bibliometric methods and drawing on city/urban tourism literature, this paper proposes a concept of tourism–industrial complex to cover current complicated and various tourism activities that are embedded in cities at diverse levels regardless of social, economic, and spatial factors. Then, four types of tourism–industrial complexes are proposed, including demand-driven, resource-dependent, externally forced, and hybrid-driven models. Due to the networked connectivity of urban tourism, urban backgrounds, tourism industry, and external circumstances all contribute to a coupling the tourism city development system. The results provide theoretical constructs and policy recommendations for optimization and sustainable city and tourism development.

The disparity of rural and urban hospital utilization has aroused much concern. With the improvement of their living standards, patients in rural areas have an emerging need for traveling across borders for better medical treatment in China. This paper reveals the medical tourism of rural residents towards urban hospitals driven by hospital needs and points out that such disparities may be caused by medical tourism. The ratio of people aged 65 and above in total rural populations was used to identify the potential target customers for medical tourism. Based on rural and urban datasets ranging from 2007&ndash, 2017 on the provincial level, this paper presents a mobile treatment model and market concentration model with an ecological foundation. The feasible generalized least squared approach was used in the estimation of the fixed-effect regressions. The study found that there was a positive and significant relationship between rural old-age ratios and urban inpatient visits from different income groups. On average, a one percent rise in rural old-age ratio would increase the inpatient visits of urban hospitals by 138 thousand persons. There was also a positive and significant relationship between the rural old-age ratio and the market concentration of urban inpatient visits. It was found that the rural old-age ratio significantly influenced the market concentration of urban inpatient visits in the middle-high income regions. The research showed that each income group from the rural aged population had participated in medical tourism, traveled to urbanized regions and made inpatient visits to urbanized medical facilities. It was also indicated that the rural aged population, especially from the middle-high income groups had a positive and significant influence on the market concentration of urban inpatient visits in the province.

The quality and scale of urbanization development are the two main aspects in China's current urbanization process. By measuring and analyzing the level differences in these two aspects, the healthy development of China&rsquo, s urbanization and urban&ndash, rural integration will be promoted. Based on the quality of urbanization and the scale of urbanization, this paper constructs an evaluation index system for urbanization coordination level. On this basis, this paper analyzes the spatial correlation, spatial difference, and spatial pattern evolution characteristics of urbanization coordination level in 286 sample cities nationwide from 2005 to 2015. Then, by introducing the spatial econometric regression model, this paper discusses the driving mechanism of the spatial and temporal evolution of urbanization coordination level. The results show that: (1) The level of coordination between urbanization quality and urbanization scale shows a strong spatial correlation in space, which is consistent with the actual development status, (2) the level of urbanization coordination shows a trend of evolution from northeast to southwest in the evolution of spatial pattern, but the extent of change is small, and (3) the spatial and temporal pattern of urbanization coordination level is affected by different driving forces, of which internal source is the primary impact factor, followed by administrative level and investment level. In addition, the level of urbanization coordination has a positive spillover effect on the level of urbanization coordination in adjacent areas.

The tightening of the financing environment and global climate change have become urgent problems for high-quality economic development all over the world. Facing these challenges, the Chinese government is committed to alleviating regional financing constraints and setting carbon-emission reduction targets. However, are these measures effective for high-quality urban development? This paper attempts to use unbalanced panel data from 290 cities on the Chinese mainland from 2004–2017 to provide an answer to the problem using a scatter plot and the mediator effect model. Results show that: (1) financing constraints limit the funds required for urban development, which is not conducive to high-quality urban development, but high-quality urban development has the characteristics of “path dependence”; (2) In the context of environmental regulation, financing constraints are mainly enacted through reducing carbon emissions, which is inconducive to high-quality urban development. Carbon emissions are the transmission mechanism whereby financing constraints affect high-quality urban development; (3) Cities with large financing constraints have insufficient capital investment for high-quality urban development, and the aggravation of financing constraints has an increasingly obvious inhibitory effect on high-quality urban development. Moreover, due to the effect of the global economic crisis in 2008, the negative effect of financing constraints on high-quality urban development had the characteristics of U-shaped fluctuation. Thus, this paper believes that the implementation of China’s double carbon policy is at the expense of high-quality urban development, and there is a long way to go before high-quality urban development reaches later stages. Other countries should carefully weigh up the relationship between environmental pollution and economic development when facing financing constraints.

Although the relationship between trade and environment has been widely discussed in past studies, trade policy has been in a state of continuous change in recent years. Previous studies have focused on the impact of trade opening or liberalization on the environment, ignoring discussion of the dynamic changes of trade policy. Therefore, it is very important to explore the connection between trade policy changes and environmental pollution for future environmental protection. In order to realize the in-depth study of this mechanism, the paper will try to solve the following three problems: (1) What is the relationship between change in trade policy uncertainty and China’s environmental pollution? (2) What is the mechanism by which trade uncertainty changes environmental pollution? (3) Due to China’s vast territory and regional differences, will changes in trade policy uncertainty have heterogeneous effects due to regional differences? To solve these problems, based on China’s accession to the WTO at the end of 2001, this paper, for the first time, uses PM2.5 concentration data of 246 prefecture-level cities in China to explore the impact of trade policy uncertainty on China’s environmental pollution, then we make an in-depth analysis of the impact path and heterogeneity of urban spatial distribution and city size. We found that, after China’s accession to the WTO, the growth rate of PM2.5 concentration reduced in cities with lower trade policy uncertainty and the inhibition effect was different due to the spatial distribution of city size. A further mechanism test shows that reduction in trade policy uncertainty can improve environmental pollution through industrial, structural and technological effects.

Based on the panel data of 285 prefecture-level cities and above in China from 2005 to 2019, this paper takes the “Broadband China” pilot policy as a quasi-natural experiment and evaluates the impact of Internet development on urban eco-efficiency (symbolized by the “Broadband China” policy) by constructing multi-period difference-in-difference (DID) and spatial DID models. Results show that: the “Broadband China” pilot policy significantly improves the urban eco-efficiency: the eco-efficiency in pilot cities is about 16.8% higher than that in other cities. The results remain consistent after testing for robustness, including using estimation methods, excluding the sample of key cities, changing core explanatory variables, and introducing instrumental variables. Next, the influence of the “Broadband China” pilot policy on eco-efficiency is characterized by significant regional heterogeneity: Internet development significantly improves the eco-efficiency in the central, eastern and northeastern regions that are economically more developed and not resource-dependent. In contrast, this effect is not obvious in the western region that is economically less developed and resource-dependent. Moreover, the influencing mechanism of Internet development on eco-efficiency suggests that the “Broadband China” strategy boosts urban eco-efficiency by increasing the Internet penetration rate, improving technological innovation capacity, and upgrading the industrial structure. In addition, results from the spatial DID models indicate that the “Broadband China” pilot policy improves the eco-efficiency in local cities and significantly enhances that in neighboring cities. Based on this, this paper puts forward some suggestions regarding promoting new network infrastructure construction and differentiating development policies to fit local conditions.

Climate emergency, landscape connectivity and rapid urbanization are among the major challenges of the 21st century. This paper discusses ways in which cities can respond to the changing climate and put in place a sustainable vision. It uses the garden city concept as a vehicle to investigate the future of our cities in relation to the climate emergency and the elements that urban centres need to provide. Cities and their wider regions are recognised as key actors in supporting systemic change and climate change governance, and therefore the scope of this paper is to explore contemporary models of garden cities and the ways in which these might be able to address climate emergency as well as the concepts of zero carbon and sustainability. The study uses the 2014 Wolfson Economics Prize, which was based on a garden city question. Taking an environmental perspective on the delivery of future cities, and using the competition essays and masterplans, this study produces analytical drawings aiming to unpack the concepts of sustainability and low carbon. This research concludes that the garden city concept can support the future needs of our settlements, but a 21st century approach needs to be developed. The social and economic ideas originally introduced at the end of the 19th century need to be updated as a holistic vision, including nature and biodiversity, climatic conditions, climate emergency adaptation and mitigation processes as well as community health and wellbeing, to be able to fully respond to the needs of the future.

Traffic accidents are of worldwide concern, as they are one of the leading causes of death globally. One policy designed to cope with them is the design and deployment of road safety systems. These aim to predict crashes based on historical records, provided by new Internet of Things (IoT) technologies, to enhance traffic flow management and promote safer roads. Increasing data availability has helped machine learning (ML) to address the prediction of crashes and their severity. The literature reports numerous contributions regarding survey papers, experimental comparisons of various techniques, and the design of new methods at the point where crash severity prediction (CSP) and ML converge. Despite such progress, and as far as we know, there are no comprehensive research articles that theoretically and practically approach the model selection problem (MSP) in CSP. Thus, this paper introduces a bibliometric analysis and experimental benchmark of ML and automated machine learning (AutoML) as a suitable approach to automatically address the MSP in CSP. Firstly, 2318 bibliographic references were consulted to identify relevant authors, trending topics, keywords evolution, and the most common ML methods used in related-case studies, which revealed an opportunity for the use AutoML in the transportation field. Then, we compared AutoML (AutoGluon, Auto-sklearn, TPOT) and ML (CatBoost, Decision Tree, Extra Trees, Gradient Boosting, Gaussian Naive Bayes, Light Gradient Boosting Machine, Random Forest) methods in three case studies using open data portals belonging to the cities of Medellín, Bogotá, and Bucaramanga in Colombia. Our experimentation reveals that AutoGluon and CatBoost are competitive and robust ML approaches to deal with various CSP problems. In addition, we concluded that general-purpose AutoML effectively supports the MSP in CSP without developing domain-focused AutoML methods for this supervised learning problem. Finally, based on the results obtained, we introduce challenges and research opportunities that the community should explore to enhance the contributions that ML and AutoML can bring to CSP and other transportation areas.

It is a key issue for the Chinese government to improve eco-efficiency and realize green development. As a spatial organization mode of industrial labor division, industrial agglomeration has a complex impact on eco-efficiency. However, it is still debatable which industrial agglomeration modes have a positive impact on eco-efficiency. This paper employs a panel threshold model, enterprise micro-level data, and relevant economic environment data from 283 cities in China from 2004 to 2012. It tests the nonlinear effects of specialized, related diversified, and unrelated diversified agglomeration on industrial eco-efficiency. The results show that the impact of specialized and related diversified agglomeration on industrial eco-efficiency is first inhibited and then promoted. The unrelated diversified agglomeration has a significantly negative impact on industrial eco-efficiency, but the negative impact weakens when agglomeration reaches a certain level. Furthermore, the impact of the three agglomeration modes on industrial eco-efficiency depends on city size. The impact of specialized agglomeration on industrial eco-efficiency is insignificant in small- and some medium-sized cities, but it has a significant inhibitory effect on industrial eco-efficiency when the city surpasses medium size. The role of related diversified agglomeration in promoting industrial eco-efficiency is further enhanced with the growth of city size. The impact of unrelated diversified agglomeration on industrial eco-efficiency gradually changes from negative to positive, but it plays a promoting role only when the city reaches the scale of super-large and mega-cities. Finally, this paper suggests that policymakers should formulate differentiated agglomeration policies according to changes in industrial agglomeration level or city size to improve industrial eco-efficiency.

Intelligent traffic management is an important issue for smart cities. City councils try to implement the newest techniques and performant technologies in order to avoid traffic congestion, to optimize the use of traffic lights, to efficiently use car parking, etc. To find the best solution to this problem, Birmingham City Council decided to allow open-source predictive traffic forecasting by making the real-time datasets available. This paper proposes a multi-agent system (MAS) approach for intelligent urban traffic management in Birmingham using forecasting and classification techniques. The designed agents have the following tasks: forecast the occupancy rates for traffic flow, road junctions and car parking; classify the faults; control and monitor the entire process. The experimental results show that k-nearest neighbor forecasts with high accuracy rates for the traffic data and decision trees build the most accurate model for classifying the faults for their detection and repair in the shortest possible time. The whole learning process is coordinated by a monitoring agent in order to automate Birmingham city’s traffic management.

With the acceleration of industrialization and urbanization, the Yangtze River Economic Belt (YREB) is facing many environmental problems that need to be solved in the process of development. This paper aims to analyze the environmental governance effects of nine provinces and two municipalities in the Yangtze River Economic Belt from 2009 to 2018. Firstly, based on the input-output index, the slacks-based measure (SBM) undesirable model and Malmquist (ML) index were used to measure the green total factor productivity (GTFP) of the YREB from 2009 to 2018. The results showed that the technological progress index contributed the most to the GTFP of the YREB, followed by the pure technical efficiency index and the scale efficiency index. Environmental regulation has no significant impact on the GTFP of the YREB. Secondly, by analyzing the effect of environmental governance in the YREB, the results show that the main reasons for the ineffective environmental governance in the YREB are the redundant input of environmental resources, excessive unwanted output, and low harmless treatment rate of municipal solid waste, rather than the low level of urban environmental management. Finally, this paper provides recommendations for the ineffective provinces and municipalities of the YREB to further optimize the input-output factors of environmental governance.

This paper shows the efficacy of a novel urban categorization framework based on deep learning, and a novel categorization method customized for cities in the global south. The proposed categorization method assesses urban space broadly on two dimensions—the states of urbanization and the architectural form of the units observed. This paper shows how the sixteen sub-categories can be used by state-of-the-art deep learning modules (fully convolutional network FCN-8, U-Net, and DeepLabv3+) to categorize formal and informal urban areas in seven urban cities in the developing world––Dhaka, Nairobi, Jakarta, Guangzhou, Mumbai, Cairo, and Lima. Firstly, an expert visually annotated and categorized 50 × 50 km Google Earth images of the cities. Each urban space was divided into four socioeconomic categories: (1) highly informal area, (2) moderately informal area, (3) moderately formal area, and (4) highly formal area. Then, three models mentioned above were used to categorize urban spaces. Image encompassing 70% of the urban space was used to train the models, and the remaining 30% was used for testing and validation of each city. The DeepLabv3+ model can segment the test part with an average accuracy of 90.0% for Dhaka, 91.5% for Nairobi, 94.75% for Jakarta, 82.0% for Guangzhou city, 94.25% for Mumbai, 91.75% for Cairo, and 96.75% for Lima. These results are the best for the DeepLabv3+ model among all. Thus, DeepLabv3+ shows an overall high accuracy level for most of the measuring parameters for all cities, making it highly scalable, readily usable to understand the cities’ current conditions, forecast land use growth, and other computational modeling tasks. Therefore, the proposed categorization method is also suited for real-time socioeconomic comparative analysis among cities, making it an essential tool for the policymakers to plan future sustainable urban spaces.

The surface urban heat island (SUHI) effect poses a significant threat to the urban environment and public health. This paper utilized the Local Climate Zone (LCZ) classification and land surface temperature (LST) data to analyze the seasonal dynamics of SUHI in Wuhan based on the Google Earth Engine platform. In addition, the SUHI intensity derived from the traditional urban–rural dichotomy was also calculated for comparison. Seasonal SUHI analysis showed that (1) both LCZ classification and the urban–rural dichotomy confirmed that Wuhan’s SHUI effect was the strongest in summer, followed by spring, autumn and winter, (2) the maximum SUHI intensity derived from LCZ classification reached 6.53 °C, which indicated that the SUHI effect was very significant in Wuhan, (3) LCZ 8 (i.e., large low-rise) had the maximum LST value and LCZ G (i.e., water) had the minimum LST value in all seasons, (4) the LST values of compact high-rise/midrise/low-rise (i.e., LCZ 1–3) were higher than those of open high-rise/midrise/low-rise (i.e., LCZ 4–6) in all seasons, which indicated that building density had a positive correlation with LST, (5) the LST values of dense trees (i.e., LCZ A) were less than those of scattered trees (i.e., LCZ B) in all seasons, which indicated that vegetation density had a negative correlation with LST. This paper provides some useful information for urban planning and contributes to the healthy and sustainable development of Wuhan.

Sustainable Development Goal (SDG) 6.2 sets an ambitious target of leaving no-one without adequate and equitable sanitation by 2030. The key concern is the lack of local human and financial capital to fund the collection of reliable information to monitor progress towards the goal. As a result, national and local records may be telling a different story of the proportion of safely managed sanitation that counts towards achieving the SDG. This paper unveils such inconsistency in sanitation data generated by urban authorities and proposes a simple approach for collecting reliable and verifiable information on access to safely managed sanitation. The paper is based on a study conducted in Babati Town Council in Tanzania. Using a smartphone-based survey tool, city health officers were trained to map 17,383 housing units in the town. A housing unit may comprise of two or more households. The findings show that 5% practice open defecation, while 82% of the housing units have some form of sanitation. Despite the extensive coverage, only 31% of the fecal sludge generated is safely contained, while 64% is not. This study demonstrates the possibility of using simple survey tools to collect reliable data for monitoring progress towards safely managed sanitation in the towns of global South.

This paper employs a unique ecosystem services analysis methodology to evaluate how cities could support or generate ecosystem services. Ecosystem services analysis can provide quantifiable goals for urban ecological regeneration that are determined by the site-specific ecology and climate of an urban area. In this research, the ecosystem service of habitat provision is the key focus. The role of urban green space and urban forests is crucial within this. Setting ambitious targets for urban ecological performance and ecosystem services provision is of great importance due to the large negative environmental impact that cities currently have on ecosystems and, therefore, ecosystem service provision, and because healthier ecosystems enable humans to better adapt to climate change through creating potentials for increased resilience. A comparative case study analysing the ecosystem service of habitat provision in two existing urban environments with similar climates (Cfb according to the K&ouml, ppen Climate Classification System) but in different parts of the world, namely Wellington, New Zealand and Curitiba, Brazil, was conducted to examine how the ecosystem services analysis concept can used to devise urban habitat provision goals. The paper concludes that, although achieving habitat provision goals derived from ecosystem services analysis in urban areas is likely to be difficult, determining quantitative site- and climate-specific staged goals could enable urban design professionals to increase the effectiveness of conservation and regeneration efforts in terms of ecosystem service provision from urban green and blue spaces.

Urban planning has been proven and is expected to promote public health by improving the built environment. With a focus on respiratory health, this paper explores the impact of the built environment on the incidence of lung cancer and its planning implications. While the occurrence of lung cancer is a complicated and cumulative process, it would be valuable to discover the potential risks of the built environment. Based on the data of 52,009 lung cancer cases in Shanghai, China from 2009 to 2013, this paper adopts spatial analytical methods to unravel the spatial distribution of lung cancer cases. With the assistance of geographic information system and Geo-Detector, this paper identifies certain built environments that are correlated with the distribution pattern of lung cancer cases in Shanghai, including the percentage of industrial land (which explains 28% of the cases), location factors (11%), and the percentages of cultivated land and green space (6% and 5%, respectively). Based on the quantitative study, this paper facilitates additional consideration and planning intervention measures for respiratory health such as green buffering. It is an ecological study to illustrate correlation that provides approaches for further study to unravel the causality of disease incidence and the built environment.

Climate change increases the risks of heat stress, especially in urban areas where urban heat islands can develop. This literature review aims to describe how severe heat can occur and be identified in urban indoor environments, and what actions can be taken on the local scale. There is a connection between the outdoor and the indoor climate in buildings without air conditioning, but the pathways leading to the development of severe heat levels indoors are complex. These depend, for example, on the type of building, window placement, the residential area’s thermal outdoor conditions, and the residents’ influence and behavior. This review shows that only few studies have focused on the thermal environment indoors during heat waves, despite the fact that people commonly spend most of their time indoors and are likely to experience increased heat stress indoors in the future. Among reviewed studies, it was found that the indoor temperature can reach levels 50% higher in °C than the outdoor temperature, which highlights the importance of assessment and remediation of heat indoors. Further, most Heat-Health Warning Systems (HHWS) are based on the outdoor climate only, which can lead to a misleading interpretation of the health effects and associated solutions. In order to identify severe heat, six factors need to be taken into account, including air temperature, heat radiation, humidity, and air movement as well as the physical activity and the clothes worn by the individual. Heat stress can be identified using a heat index that includes these six factors. This paper presents some examples of practical and easy to use heat indices that are relevant for indoor environments as well as models that can be applied in indoor environments at the city level. However, existing indexes are developed for healthy workers and do not account for vulnerable groups, different uses, and daily variations. As a result, this paper highlights the need for the development of a heat index or the adjustment of current thresholds to apply specifically to indoor environments, its different uses, and vulnerable groups. There are several actions that can be taken to reduce heat indoors and thus improve the health and well-being of the population in urban areas. Examples of effective measures to reduce heat stress indoors include the use of shading devices such as blinds and vegetation as well as personal cooling techniques such as the use of fans and cooling vests. Additionally, the integration of innovative Phase Change Materials (PCM) into facades, roofs, floors, and windows can be a promising alternative once no negative health and environmental effects of PCM can be ensured.

The Urban Heat Islands (UHI) effect is a microclimatic phenomenon that especially affects urban areas. It is associated with significant temperature increases in the local microclimate, and may amplify heat waves. Due to their intensity, UHI causes not only thermal discomfort, but also reductions in the levels of life quality. This paper reviews the important role of green infrastructure as a means through which the intensity of UHI may be reduced, along with their negative impact on human comfort and wellbeing. Apart from a comprehensive review of the available literature, the paper reports on an analysis of case studies in a set of 14 cities in 13 countries representing various geographical regions and climate zones. The results obtained suggest that whereas UHI is a common phenomenon, green infrastructure in urban areas may under some conditions ameliorate their impacts. In addition, the study revealed that the scope and impacts of UHI are not uniform: depending on peculiarities of urban morphologies, they pose different challenges linked to the microclimate peculiar to each city. The implications of this paper are threefold. Firstly, it reiterates the complex interrelations of UHIs, heat waves and climate change. Secondly, it outlines the fact that keeping and increasing urban green resources leads to additional various benefits that may directly or indirectly reduce the impacts of UHI. Finally, the paper reiterates the need for city planners to pay more attention to possible UHI effects when initiating new building projects or when adjusting current ones. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Governance, and specifically local management and institutional systems, is among the key factors affecting the management of World Heritage (WH) properties in urban contexts. The adoption of the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL approach) promotes a governance reform towards more inclusive and integrated management. The purpose of this paper is to discuss how the HUL approach may help to solve the key governance challenges affecting WH in urban contexts. The governance of WH in three European cities is compared. Edinburgh, Porto, and Florence were chosen for their familiarity with the HUL approach and willingness to provide guidance and review policies and review their policies as management plans. The methodology includes a policy analysis of the management plans followed by a comparative analysis based on the six key governance challenges addressed in the recent literature. The results show that the HUL approach is supporting the governance of WH in urban contexts, and that more inclusive and integrated management has helped address the challenges affecting heritage management.

Water, energy, and food are the most important basic resources for economic and social development. In the context of global population growth, environmental degradation, and resource shortages, the interrelationship between the water, energy, and food has become increasingly important. In this paper, the city of Ordos in China was selected as a study area. Firstly, this paper sorted out relevant research literature and fully understood the concept of water-energy-food (WEF) nexus. Then, an optimization model of WEF system was constructed based on interval number multi-objective programming, which took the comprehensive coordination deviation degree of the WEF system security and carbon dioxide emission minimization as the target. At the same time, the optimization model was constructed with full consideration of constraints such as economic benefit, water resource consumption, energy production, food production and environmental pollution emission. The results showed that the production of coal, thermal power, hydropower, wind power, and food all show an upward trend. Among them, the production of hydropower has the largest change, and the food production has the smallest change. In terms of water resource utilization, food production has the largest allocation of water resources accounting for nearly 80%, followed by coal production, thermal power generation and hydropower generation. The smallest allocation is natural gas. In particular, the allocation of water for coal production and hydroelectric power generation has increased significantly. Finally, the policy recommendations were put forward to promote the sustainable development of WEF system in Ordos. The optimization research on the WEF system can help to ensure the WEF system security in Ordos and promote the sustainable development of WEF system, which also can provide reference for other regions.

In recent years, artificial intelligence (AI) has started to manifest itself at an unprecedented pace. With highly sophisticated capabilities, AI has the potential to dramatically change our cities and societies. Despite its growing importance, the urban and social implications of AI are still an understudied area. In order to contribute to the ongoing efforts to address this research gap, this paper introduces the notion of an artificially intelligent city as the potential successor of the popular smart city brand—where the smartness of a city has come to be strongly associated with the use of viable technological solutions, including AI. The study explores whether building artificially intelligent cities can safeguard humanity from natural disasters, pandemics, and other catastrophes. All of the statements in this viewpoint are based on a thorough review of the current status of AI literature, research, developments, trends, and applications. This paper generates insights and identifies prospective research questions by charting the evolution of AI and the potential impacts of the systematic adoption of AI in cities and societies. The generated insights inform urban policymakers, managers, and planners on how to ensure the correct uptake of AI in our cities, and the identified critical questions offer scholars directions for prospective research and development.

Compact cities and their urban forms have implications on sustainable city development because of high density urban settlement, increased accessibility, and a balanced land use mix. This paper uses quantitative means of understanding urban morphological characteristics with reference to the differing qualities of the urban form (i.e., street patterns, building volumes, land uses and greenery). The results, based on 89 neighborhood communities of Hong Kong, show varying degrees of regional differences in the urban built form supported by numerical statistics and graphical illustrations. This paper offers empirical evidence on some morphological characteristics that can be estimated objectively using modern geospatial technologies and applied universally to inform urban planning. However, more studies linking these quantifiable measures of the physical form with sustainable urban living are needed to account for human comfort in the totality of environmental, social, and economic responsibilities.

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management.

The land development by human beings has changed from the initial small-scale and low-level transformation to the comprehensive utilization of large-scale and high-intensity implementations. The contradiction between production-living-ecology space (PLES) has become increasingly prominent while drawing land dividends. As one of the important birthplaces of Chinese civilization and the ecological barrier in the northern region, the rapid urbanization and industrialization of the Yellow River Basin (YRB) make the ecological environment very fragile, and the imbalance of land and space development is extremely serious. Therefore, according to the multifunctional characteristics of land use, this paper establishes a classification system of production space (PS), living space (LS) and ecology space (ES), and discusses the spatiotemporal evolution and conflict distribution characteristics of the PLES with the help of the transfer matrix and spatial conflict index (SCI). The results are as follows. In 1990–2020, agricultural production space (APS), grassland ecology space (GES) and other ecology space (OES) yielded the largest proportion of PLES in the YRB. However, compared with 1990, the area of these spatial types decreased in 2020, while the urban living space (ULS) expanded rapidly. The distribution pattern of PLES was generally consistent, and the transformation between PLES in Ningxia, central Inner Mongolia, Loess Plateau and downstream areas was relatively intense. The conflict index of PLES showed an upward trend, but it was generally in a controllable range. The stable and controllable areas were concentrated in the upstream of the urban agglomeration, and the midstream and downstream were basic out of control and seriously out of control, respectively.