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The aim of this paper is to explore whether and how urban road transport (URT) development affects haze pollution. One of the innovations of this paper is that URT development is measured by road accessibility with novel digital elevation model datasets, which have been used by few scholars. The endogenous problem caused by revere causality issue in the relationship between URT development and haze pollution is also considered. Based on the panel data of prefecture-level cities of Yangtze River Delta (YRD) region in China from 2011 to 2018, this paper uses long-lagged values of URT development as the instrumental variable, employing the two-stage least squares (2SLS) method. The study shows that URT development leads to an increase of haze pollution. Moreover, mechanism tests based on moderating and mediating models support the finding that decreasing haze pollution resulted from better connection effects, while rising agglomeration effects tend to bring about increasing haze pollution, and the latter effect is larger in magnitude than the former. Current URT development may have long-term negative consequences for livability of YRD cities, and urban decision makers should reconsider the effectiveness of the current road transport investment and construction. [ABSTRACT FROM AUTHOR]

Comparing with cities, rural communities especially those declining rural communities have become vulnerable to natural disasters owing to their backward socioeconomic conditions. Taking Xun County of China's Henan Province as the study area, the paper aims to evaluate rural community resilience to flood by unveiling the connection between individuals' cognition, follow-up actions and the community resilience. Research results show that: (1) The logic chain exists as individual's cognition to disaster leads to their constructive actions to cope with disaster, which contribute to community resilience. (2) At the cognition dimension, individual's knowledge reserve of disaster prevention and their recognition to local authority are playing an important role in their decision making and follow-up behaviors when disaster occurs. (3) At the action dimension, individual's familiarity with the disaster preparedness, efficient information transmission when disaster occurs and villagers' following order and their unity of action all contribute to community resilience to disaster. The paper proposes ways to improve rural community resilience to disasters based on the research findings. [ABSTRACT FROM AUTHOR]

Against the backdrop of digitization and global warming, fintech plays a crucial role in accelerating the growth of green finance, driving innovation in the financial industry, and catalyzing the low-carbon transformation of economic activities. This paper utilizes city panel data from 2007 to 2019 to examine the direct impact of fintech on carbon emission efficiency (CEE), the transmission channels of green technological innovation and green finance, and the spatial spillover effects, using dynamic panel models, mediation effect models, and dynamic spatial Durbin models (SDM). The study finds that: (i) Fintech significantly improves CEE, and this conclusion remains robust after accounting for potential endogeneity issues and conducting robustness tests. (ii) Mechanism analysis reveals that green finance and green technological innovation are the primary channels through which fintech influences CEE. (iii) Results from the dynamic SDM model indicate that fintech has a significant positive spatial spillover effect on CEE, with the long-term spillover effect being smaller than the short-term spillover effect. (iv) Heterogeneity analysis reveals that fintech's improvement effect on CEE is mainly evident in eastern regions, emerging first-tier and first-tier cities, and non-resource-based cities. Our research provides new insights for policymakers on achieving China's dual-carbon goals through the promotion of fintech development, green finance, and green technological innovation. It also aids in the coordinated development of fintech among cities and the formulation of differentiated policies, providing a theoretical foundation and empirical support for future research. [ABSTRACT FROM AUTHOR]

In this paper, we have provided more insights on the relationship between under five morbidity in Nigeria and some background characteristics using a Poisson regression model and the most recent 2018 NDHS data on Acute Respiratory Infection (ARI), diarrhoea and fever. Some of our results are that children 36–47 months old have the highest risk of ARI [OR = 1.45; CI (1.31,1.60)] while children less than 6 months old have the lowest risk of ARI [OR = 0.14; CI (0.11,0.17)]. The prevalence of diarrhoea is generally high among children under 48-59 months old but highest among children 6–11 months old [OR = 4.34; CI (3.69,5.09)]. Compared to children 48–59 months old, children in all other age categories except 24–34 months old have a high risk of fever [OR = 0.95; CI (0.73,1.24)]. ARI is more prevalent among female children [OR = 8.88; CI (8.02,9.82)] while diarrhoea [OR = 21.75; (19.10,24.76)] and fever [OR = 4.78; CI (4.31,5.32)] are more prevalent among male children. Children in urban areas are more likely to suffer ARI [OR = 9.49; CI (8.31,10.85)] while children in rural areas are more likely to suffer both diarrhoea [OR = 21.75; CI (19.10,24.76)] and fever [OR = 4.90; CI (4.26,5.63)]. Children in the South-South have the highest risk of ARI [OR = 4.03; CI (3.65,4.454)] while children in the North Central have the lowest risk of ARI [OR = 1.55; CI (1.38,1.74)] and highest risk of diarrhoea [OR = 3.34; CI (2.30,5.11)]. Children in the Northeast have the highest risk of fever [OR = 1.30; CI (1.14,1.48)]. In the Northcentral region, Kogi state has the highest prevalence of fever [OR = 2.27; CI (1.62,3.17)], while Benue state has the lowest [OR = 0.35; CI (0.20,0.60)]. Children in Abuja state face similar risks of fever and diarrhoea [OR = 0.84; CI (0.55,1.27)], with the risk of diarrhoea in Abuja being comparable to that in Plateau state [OR = 1.57; CI (0.92,2.70)]. Nasarawa state records the highest incidence of diarrhoea in the Northcentral [OR = 5.12; CI (3.03,8.65)], whereas Kogi state reports the lowest [OR = 0.29; CI (0.16,0.53)]. In the Northeast, Borno state has the highest rate of fever [OR = 3.28; CI (2.80,3.84)], and Bauchi state the lowest [OR = 0.38; CI (0.29,0.50)]. In Adamawa state, the risks of fever and diarrhoea are nearly equivalent [OR = 1.17; CI (0.97,1.41)], and the risk of fever there is similar to that in Taraba state [OR = 0.92; CI (0.75,1.12)]. Diarrhoea is most prevalent in Yobe state [OR = 3.17; CI (2.37,4.23)] and least prevalent in Borno state [OR = 0.26; CI (0.20,0.33)]. In the Northwest, the risk of fever is similarly high in Zamfara and Kebbi states [OR = 1.04; CI (0.93,1.17)], with Kastina state showing the lowest risk [OR = 0.39; CI (0.34,0.46)]. Children in Zamfara state experience notably different risks of fever and diarrhoea [OR = 0.07; CI (0.05,0.10)]. Kaduna state reports the highest incidence of diarrhoea [OR = 21.88; CI (15.54,30.82)], while Kano state has the lowest [OR = 2.50; CI (1.73,3.63)]. In the Southeast, Imo state leads in fever incidence [OR = 8.20; CI (5.61,11.98)], while Anambra state has the lowest [OR = 0.40; CI (0.21,0.78)]. In Abia state, the risk of fever is comparable to that in Enugu state [OR = 1.03; CI (0.63,1.71)], but the risks of fever and diarrhoea in Abia differ significantly [OR = 2.67; CI (1.75,4.06)]. Abia state also has the highest diarrhoea rate in the Southeast [OR = 2.67; CI (1.75,4.06)], with Ebonyi state having the lowest [OR = 0.05; CI (0.03,0.09)]. In the South-South region, Bayelsa and Edo states have similar risks of fever [OR = 1.28; CI (0.84,1.95)], with Akwa Ibom state reporting the highest fever rate [OR = 4.62; CI (3.27,6.52)] and Delta state the lowest [OR = 0.08; CI (0.02,0.25)]. Children in Bayelsa state face distinctly different risks of fever and diarrhoea [OR = 0.56; CI (0.34,0.95)]. Rivers state shows the highest incidence of diarrhoea in the South-South [OR = 10.50; CI (4.78,23.06)], while Akwa Ibom state has the lowest [OR = 0.30; CI (0.15,0.57)]. In the Southwest, Lagos and Osun states have similar risks of fever [OR = 1.00; CI (0.59,1.69)], with Ogun state experiencing the highest incidence [OR = 3.47; CI (2.28,5.28)] and Oyo state the lowest [OR = 0.18; CI (0.07,0.46)]. In Lagos state, the risks of fever and diarrhoea are comparable [OR = 0.96; CI (0.57,1.64)], and the risk of diarrhoea is similar to those in Ekiti, Ogun, and Ondo states. Oyo state has the highest diarrhoea rate in the Southwest [OR = 10.99; CI (3.81,31.67)], with Ogun state reporting the lowest [OR = 0.77; CI (0.42,1.42)]. Children of mothers with more than secondary education are significantly less likely to suffer ARI [OR = 0.35; CI (0.29,0.42)], whereas children of mothers without any education run a higher risk of diarrhoea [OR = 2.12; CI (1.89,2.38)] and fever [OR = 2.61; CI (2.34,2.91)]. Our analysis also indicated that household wealth quintile is a significant determinant of morbidity. The results in this paper could help the government and non-governmental agencies to focus and target intervention programs for ARI, diarrhoea and fever on the most vulnerable and risky under five groups and populations in Nigeria. [ABSTRACT FROM AUTHOR]

Carbon emission reduction is crucial for mitigating global climate change, and green fiscal policies, through providing economic incentives and reallocating resources, are key means to achieve carbon reduction targets. This paper uses data covering 248 cities from 2003 to 2019 and applies a multi-period difference-in-differences model (DID) to thoroughly assess the impact of energy conservation and emission reduction (ECER) fiscal policies on enhancing carbon emission (CE1) reduction and carbon efficiency (CE2). It further analyzes the mediating role of Green Innovation (GI), exploring how it strengthens the impact of ECER policies. We find that: (1) ECER policies significantly promote the improvement of carbon reduction and CE2, a conclusion that remains robust after excluding the impacts of concurrent policy influences, sample selection biases, outliers, and other random factors. (2) ECER policies enhance CE1 reduction and CE2 in pilot cities by promoting green innovation, and this conclusion is confirmed by Sobel Z tests. (3) The effects of ECER policies on CE1 reduction and the improvement of CE2 are more pronounced in higher-level cities, the eastern regions and non-resource cities. This research provides policy makers with suggestions, highlighting that incentivizing green innovation through green fiscal policies is an effective path to achieving carbon reduction goals. [ABSTRACT FROM AUTHOR]

In the process of global urban development, there are urgent ecological security and environmental pollution problems, green development is the fundamental way for urban sustainable development, economic transformation and mitigation of ecological and environmental problems. Based on the panel data of 283 cities at prefecture level and above in China from 2003 to 2017, this paper analyzes spatial–temporal evolution characteristics of urban green development efficiency (UGDE) and the peer effects of UGDE between cities of different grades. It is found that during the study period, in terms of temporal evolution, the average UGDE in China increased from 0.47 in 2003 to 0.61 in 2017, with a cumulative growth rate of 29.79%, showing a rising trend in general. In terms of spatial evolution, the number of low-efficiency cities and medium-efficiency cities continued to decrease. The eastern region has always been the main distribution area of higher-efficiency cities and high-efficiency cities; in the central region, UGDE in most cities improved significantly; in the western region, UGDE has always lagged behind that in the eastern and central regions. In addition, the center of gravity of UGDE presented a trend of northwest migration in general, with a total displacement of 100.07 km, and UGDE showed a spatial dispersion trend. The empirical results indicate that the improvement of UGDE in large cities has a driving effect on that in neighboring medium cities and small cities through the positive peer effect, and the growth of UGDE in medium cities has a promoting effect on that in neighboring small cities through the positive peer effect; the increase of UGDE in medium cities has a positive peer effect on that in neighboring large cities, and the growth of UGDE in small cities has a positive peer effect on that in neighboring medium cities; UGDE promotes each other between large cities through the positive peer effect. [ABSTRACT FROM AUTHOR]

The study of walkability is of great significance to the construction of healthy cities. In this paper, taking 1283 articles of walkability, which were included in Web of Science, as the research object. This paper adopts to analysis the research progress by using the method of scientometrics and knowledge networks analysis. Objectively and systematically analyze the research progress of walkability abroad from the aspects of publication overview, knowledge foundation, research direction and hot spots, etc. It is found that foreign researches on walkability mainly include three core directions: walkability and physical activity, walkability evaluation, walkability and urban design. Among them, walkability and physical activity orientation have been studied from various perspectives, such as various groups, various environmental types, different behavioral patterns and various chronic diseases. With the increasingly prominent urbanization problems and the rapid development of new technologies, multiple data, new methods and interdisciplinary cooperation will actively promote the vigorous development of walking suitability research. [ABSTRACT FROM AUTHOR]

Drones play an important role in modern cities, they bring convenience but also bring corresponding risks. Falling drones can cause casualties or damage to urban facilities and serious property damage, which increases the third-party risk problem. An effective way to reduce these third-party risks is to avoid high-risk areas in path planning, but most current path planning methods are optimized to minimize flight distance, and third-party risk costs are rarely considered. In this paper, a comprehensive risk-cost UAV path planning method is proposed, which evaluates urban risk by establishing a third-party risk model that incorporates obstacle risk, death risk, and property loss risk. This paper proposes a Min-cost A* algorithm based on city risk assessment, and smooths the generated low-risk path through the improved Floyd algorithm. The results show that the path planning method can effectively reduce the risk in the flight path, improve the reliability of the UAV flight path in the urban environment, and solve the problem of planning the third-party risk path of the UAV. [ABSTRACT FROM AUTHOR]

Green finance (GF) is recognized as a key driver of sustainable development. While existing studies have extensively discussed the relationship between GF and the Sustainable Development Goals (SDGs), few have explored the coupling coordination relationship between GF and SDGs. In this paper, we use data from thirty Chinese provinces (municipalities and autonomous regions) from 2008–2021 to examine the degree of coupling coordination development (CCD) between GF and the SDGs systems using the CCD model. We find that most SDGs and their sub-goals exhibit a significant upward trend, except for SDG8, 14–16. GF presents a fluctuating upward trend, with a significant decline in 2010 and 2019. The CCDs between GF and SDGs and their sub-goals generally show an M-shaped upward trend in most regions, with most of them experiencing a synchronous decline in 2011–2012 and 2019. In the analysis of regional heterogeneity, the eastern region performs better in SDG8–9, the central region performs better in SDG3, 14–15, while the western region performs better in SDG7. This paper provides empirical evidence for a further in-depth understanding of the relationship between GF and SDGs, which can contribute to advancing GF development and the SDG process. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]

Air pollution is a serious problem that affects economic development and people's health, so an efficient and accurate air quality prediction model would help to manage the air pollution problem. In this paper, we build a combined model to accurately predict the AQI based on real AQI data from four cities. First, we use an ARIMA model to fit the linear part of the data and a CNN-LSTM model to fit the non-linear part of the data to avoid the problem of blinding in the CNN-LSTM hyperparameter setting. Then, to avoid the blinding dilemma in the CNN-LSTM hyperparameter setting, we use the Dung Beetle Optimizer algorithm to find the hyperparameters of the CNN-LSTM model, determine the optimal hyperparameters, and check the accuracy of the model. Finally, we compare the proposed model with nine other widely used models. The experimental results show that the model proposed in this paper outperforms the comparison models in terms of root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The RMSE values for the four cities were 7.594, 14.94, 7.841 and 5.496; the MAE values were 5.285, 10.839, 5.12 and 3.77; and the R2 values were 0.989, 0.962, 0.953 and 0.953 respectively. [ABSTRACT FROM AUTHOR]

With the popularity of shared bicycles in urban areas, more and more residents choose this fast and convenient mode of transportation for short-distance travel. By optimizing the layout of shared bicycle parking areas and delivery quantity, the investment cost of shared bicycle enterprises can be effectively reduced, and the convenience of residents' travel can be improved at the same time. In this paper, we develop a collaborative optimization model for the layout of the shared bicycle parking area and delivery quantity, aiming at minimizing the walking distance of residents and the investment cost of enterprises, while considering the constraints of the parking area's attractive range and the number of bicycles placed. Aiming at the characteristics of this mixed integer nonlinear problem, an improved genetic algorithm incorporating symmetric individual precision control mechanism is designed. Finally, taking the planned area between the Second Ring Road and the Third Ring Road in the northern part of Jin-niu District, Chengdu as the background, the proposed collaborative optimization model for the layout of shared bicycle parking areas and delivery quantity is applied to a real scene. The results show that after optimization, the number of parking areas is reduced by 2, and the total investment cost is reduced by about 12.2%. [ABSTRACT FROM AUTHOR]

Information and communication technology plays an essential role in affecting CO2 emissions and promoting green and sustainable development. This paper empirically examines the effect of the level of urban ICT development on CO2 emissions using panel data for Chinese cities from 2010 to 2020. On this basis, a spatial Durbin model is used to analyze the spatial spillover effects of ICT development level affecting regional CO2 emissions, and its direct, indirect and overall effects are further analyzed. The conclusions of the study are as follows. (1) The CO2 emissions of Chinese cities are correlated by spatial distance and show high-high or low-low clustering characteristics. (2) ICT development can reduce CO2 emissions in the region and increase CO2 emissions in neighboring regions. This conclusion still holds after several robustness tests. And when the level of ICT development increases by 1 standard deviation, CO2 emissions are reduced by 64%. (3) The mechanism of action shows that ICT can influence regional CO2 emissions through its technological innovation effect and industrial upgrading effect. (4) The impact of ICT development on regional carbon emissions is characterized by significant heterogeneity depending on the city's geographical location and whether or not environmental information is publicly available. [ABSTRACT FROM AUTHOR]

In this paper, the adoption of SO2 emission tax rates higher than the legal minimum standard is regarded as a noteworthy policy reform in China (quasi-natural experiment), and a spatial Difference-in-Differences (Spatial-DID) model is constructed to test the direct effects (local effects) and indirect effects (spatial spillover effects) of SO2 emission tax policy reform on PM2.5 concentrations in the atmosphere of 285 China's cities. The estimation and calculation results of the Spatial-DID model show that the SO2 emission tax policy reform can significantly reduce local PM2.5 concentration and significantly promote PM2.5 concentration in surrounding areas. The results of heterogeneity analysis show that the SO2 emission tax policy reform can produce a relatively more beneficial spatial spillover effect in eastern cities and higher administrative level cities, while the pollutants emission rights trading and the reform of NOx emission tax rates can produce beneficial spatial spillover effects when cooperating with the reform of SO2 emission tax rates. The results of the mediation effect analysis show that the higher SO2 emission tax rate can aggravate the surrounding PM2.5 pollution by promoting the aggregation level of industrial production factors and the industrial SO2 emission intensity in the surrounding areas, which can support the existence of the pollution heaven effect. [ABSTRACT FROM AUTHOR]

Existing research rarely examines the subjective and objective built environment of river valley-type cities in relation to travel mode choice, particularly overlooking the heterogeneity among travelers in these cities. In this paper, based on questionnaire survey data and built environment data, terrain spatial perception (TSP) is introduced to expand the theory of planned behavior (TPB), and a Structural Equation Model (SEM) is established. Factor analysis and path analysis are conducted using SPSS and AMOS to estimate latent variables. An integrated model of SEM and random parameter Logit model (RPLM), which can not only analyze the psychological perception factors of commuters in river valley-type cities but also consider the heterogeneity of psychological perception, was constructed to analyze the impact of personal attributes, objective built environment factors, and psychological latent variables on the commuting mode choice behavior of public transport users in river valley-type cities. The results indicate that the five observation indicators corresponding to the proposed terrain spatial perception latent variables can better explain the terrain spatial perception of commuters in river valley-type cities. Different from plain cities, the subjective and objective built environment of river valley-type cities notably influence the travel behavior of commuters. Moreover, the parameters of terrain spatial perception follow a normal distribution, indicating that the sensitivity of different commuters to the terrain spatial perception of river valley-type cities is heterogeneous. The results of our study can provide a reference for alleviating traffic issues in valley cities. [ABSTRACT FROM AUTHOR]

There are urgent ecological and environmental problems in the process of the utilization of urban construction land, promoting green utilization of construction land is conducive to urban sustainable development and high-quality economic development. Based on the panel data of 108 prefecture-level and above cities in the Yangtze River Economic Belt, China from 2003 to 2017, this paper uses the super-efficiency SBM model to measure the green efficiency of urban construction land (GEUCL), analyzes its spatial–temporal evolution characteristics, and constructs the spatial autoregressive model to study its spatial spillover effects from the perspective of urban hierarchy. It is found that, in terms of temporal variation, the average efficiency value shows a fluctuating upward trend during the study period, rising from 0.27 in 2003 to 0.39 in 2017, the cumulative growth rate is 44.44%, with an average annual growth rate of 3.14%. In terms of spatial distribution characteristics, during the study period, the number of medium-efficiency and high-efficiency cities increases significantly, while the number of low-efficiency cities decreases sharply; high-efficiency cities always present scattered distribution, while medium-efficiency cities change from scattered distribution to agglomeration distribution. In addition, GEUCL has significantly positive spatial spillover effects between neighboring cities of different grades and between neighboring cities of the same grade, among them, the increase of GEUCL in higher-grade cities has significantly positive spatial spillover effects on that in adjacent lower-grade cities; the increase of GEUCL in lower-grade cities has significantly positive spatial spillover effects on that in neighboring higher-grade cities; GEUCL has significantly positive spatial spillover effects between neighboring cities of the same grade. [ABSTRACT FROM AUTHOR]

In this paper, we discussed the impossibility of achieving zero-covid cases per day for all time with the help of fuzzy theory, while how a single case can trigger chaotic situation in the nearby city is elaborated using multi-scrolls. To accomplish this goal, we consider the number of new cases per day; x 1 to be the preferred state variable by restricting its value to the interval (0, 1). One can need to think of x 1 as a member of a fuzzy set and provide that set with appropriate membership functions. Moreover, how a single incident in one city can spread chaos to other cities is also addressed at length, using multi-scroll attractors and the signal excitation function. In addition, a bifurcation diagram of daily new instances vs the parameter α 1 is shown, elaborating that daily new cases may show a decrease under strict rules and regulations, but can again lead to chaos. Apart from biologist, this paper can play vital role for engineers as well in a sense that, a signal function can be embedded in non-symmetric systems for the creation of multi-scroll attractors in all directions using a generalized algorithm that has been designed in the current work. Finally, it is our future target to show that the covid is leading towards influenza and will be no more dangerous as was in the past. [ABSTRACT FROM AUTHOR]

The problem of sky pollution with artificial light currently affects practically all branches that are related to the broadly understood environment. This is especially true for astronomical observations. This paper presents the results of measurements of the surface brightness of the night sky for the city of Rzeszów and the surrounding area, which were made in 2015, 2018 and 2021 using the photometer Sky Quality Meter (SQM-L). The measurements show that the surface brightness of the night sky in Rzeszów in 2015 was in the range from 19.20 to 18.67 mag/arcsec2, in 2018 the value of brightness oscillated in the range from 18.53 to 16.47 mag/arcsec2, and in 2021 this value was in the range from 17.13 by 15.11 mag/arcsec2. Translating the obtained values on the Bortle scale, we can see an increase in the brightness of the night sky from class VI in 2015 to class IX in 2021. A similar trend applies to neighboring towns, for which an increase in brightness from class IV in 2015 to class VIII in 2021 was also observed. An increase in the surface brightness of the night sky causes a deterioration or even loss of visibility of astronomical objects in the night sky. This is especially true for comets and low-brightness stars. Based on the measurement results, a forecast of the development of light pollution was prepared for the study areas until 2025. This forecast shows that we will still have to deal with an increase in the surface brightness of the night sky. Due to the further projected increase in the brightness of the night sky, it should be expected that observers in small towns will experience changes in the quality of the sky over the coming years, which will undoubtedly make astronomical observations difficult, in particular for faint celestial bodies such as comets. [ABSTRACT FROM AUTHOR]

Researchers have addressed uncertainty in multicriteria decision making from the perspective of the performance values of the alternatives, weighting of the evaluation criteria, and the evaluation methods. Still, they are yet to address the uncertainty caused by the normalization approach. In this paper, we show that different normalization methods, namely sum normalization, min–max normalization, vector normalization, and maximization normalization, can result in different rankings of the alternatives while the performance values and weights are unchanged. We applied the grey system theory to address the problem of uncertainty in this study from three aspects: alternative performance values measurement, criteria weighting, and decision matrix/table normalization within a period. The grey hybrid normalization method is proposed as the main contribution in this paper. Then, we present the rankings of 48 cities under uncertainty to decide the location of a branch office of a Chinese electric vehicle manufacturer as a practical example based on the grey entropy weighting method and grey relational analysis with positive and negative references (GRA-PNR) within the period from the year 2019 to 2021. The research results using this approach ranked New York City the best, with a stock market capitalization of economy validity as the top contributor in terms of weighting. Finally, we used simple additive weighting with grey value and the technique for order of preference by similarity to ideal solution with grey value methods to validate the study results. [ABSTRACT FROM AUTHOR]

As cities have grown, conductor rail power supplies have been widely used in the field of urban rail transit. In order to improve the running performance of trains and reduce the occurrence of accidents, it is necessary to understand the vibration of shoegear-rail system under different initial contact forces and explore the dynamic performance of shoegear-rail system. Therefore, according to the structure of shoegear-rail system, a coupling model of shoegear-rail system is established in this paper. On the basis of the model, the numerical simulation of the shoegear-rail system under different initial contact forces is carried out, and finally the vibration data of the shoegear-rail system under different initial contact forces are obtained. The results show that with the increase of initial contact force in the range of 70–160 N, the vibration amplitude of the electric shoegear and the fluctuation amplitude of the contact force increase, but the maximum absolute shear force value of the conductor rail decreases. It indicates that the lower initial contact force, the better the performance of shoegear-rail system. [ABSTRACT FROM AUTHOR]

Aerial image data are becoming more widely available, and analysis techniques based on supervised learning are advancing their use in a wide variety of remote sensing contexts. However, supervised learning requires training datasets which are not always available or easy to construct with aerial imagery. In this respect, unsupervised machine learning techniques present important advantages. This work presents a novel pipeline to demonstrate how available aerial imagery can be used to better the provision of services related to the built environment, using the case study of road traffic collisions (RTCs) across three cities in the UK. In this paper, we show how aerial imagery can be leveraged to extract latent features of the built environment from the purely visual representation of top-down images. With these latent image features in hand to represent the urban structure, this work then demonstrates how hazardous road segments can be clustered to provide a data-augmented aid for road safety experts to enhance their nuanced understanding of how and where different types of RTCs occur. [ABSTRACT FROM AUTHOR]

The ICT service industry has become a burgeoning industry at a high and stable speed. Their equitable distribution can improve national and global positive peace. This paper aimed to verify the characteristics of spatio-temporal evolution and its influencing factors in the ICT service industry. Based on the data from 31 Provinces in China from 2015 to 2019, this paper uses location quotient, spatial autocorrelation methods and spatial econometric analysis to explore the development characteristics, evolution and influencing factors of the ICT service industry, respectively. The main results are shown as follows: (1) China's ICT service industry is mainly concentrated in Beijing, Shanghai, Zhejiang, Tibet, and Guangdong, with a trend of specialisation development. They are not only distributed in cities with relatively superior overall development but also those with superior industrial and development carrier elements. Technological relevance, aggregation, and political difference might have an impact on promoting the emergence and development of these industries. (2) ICT service industry is characterised by stable and highly concentrated development. Numbers between three to five significant provinces and types with high-high (HH) and high-low (HL) clusters of local spatio-temporal association kept stable in the period. The HH was in eastern coastal areas, including Zhejiang, Shanghai, Jiangsu, and Shandong, and the HL was in Guangdong in 2015. There is a definite spatial correlation in spatial distribution with constant strengthening. (3) TUR, NDN, MIAT and the area were shown to have a significant role in promoting the ICT service industry, while NW, GDP and ICT Employment were shown to have a significant negative impact on this industry. Correspondingly, two strategies were put forward here: (1) accelerating the inter-provincial networking development of the ICT service industry, and (2) strengthening government policy guidance for the ICT service industry. These outcomes can not only provide a scientific basis and theoretical support for the distribution of strategies and resources for these industries at the theoretical level but also improve resource integration from the national perspective and the efficiency of resource use at the practical level. [ABSTRACT FROM AUTHOR]

"This paper is supported by the National Social Science Foundation of China Project Number: 21JBY179." now reads: "This paper is supported by the National Social Science Foundation of China Project Number: 21BJY179." Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-023-40954-4, published online 23 August 2023 The original version of this Article contained an error in the Funding section. [Extracted from the article]

Pedestrian-oriented urban strategies such as the Paris 15-minute City are needed to respond to the global boiling. Quantitative evaluation of pedestrian-oriented urban objectives is important for various cities, and in this paper, a walkability evaluation system for the advanced model is developed considering the characteristics of a large city. The system calculates the walkability of Seoul. The evaluation system uses the Betweenness index as a weight in the urban network analysis. Considering stations with a high betweenness in urban traffic is essential for evaluating a pedestrian-oriented metropolis. Our findings in this study are that the UNA index in WES is critical for transit-oriented, walkable cities. The large city needs to find the location for mobility hubs or stations to observe the last mile. Installing a mobility hub or station at a high-value location in the city center is functionally important. In a pedestrian-oriented city, citizens can walk and bike the last mile in a busy city center. Walkable cities can encourage active transport and ultimately create more sustainable and environmentally friendly transportation systems. This study offers valuable insights into pedestrian infrastructure, urban systems, and policies that promote green transportation. [ABSTRACT FROM AUTHOR]

A diet high in sodium contributes to a significant proportion of Disability Adjusted Life Years (DALYs) due to cardiovascular diseases. This paper describes the awareness, behaviour and determinants related to dietary salt intake in an adult population of 18–69 years that were assessed as part of the National NCD Monitoring Survey (NNMS) in India. A sub-sample of 3000 adults selected through simple random sampling from 150 nationally representative Primary Sampling Units (PSUs) was included. Data regarding awareness and behaviour related to dietary salt intake were collected. Urinary sodium excretion in spot urine samples was estimated and used to calculate dietary salt intake. The dietary salt intake's sociodemographic, behavioural and metabolic determinants were also analysed. Less than one-third of the adults of both genders in all age groups in rural and urban areas were aware that daily high salt intake could affect health. The estimated mean daily salt intake was 8.0 g (8.9 g/day for men and 7.1 g/day for women). The salt intake was significantly higher in men [Adjusted OR = 17.66 (5.24–59.46)], rural areas [Adjusted OR = 6.14 (1.83–20.60)], overweight and obese respondents [Adjusted OR = 17.62 (3.17–98.07)]. The perception of the harmful effects of high salt intake and practices to limit salt intake was low in the study population. The mean daily salt intake was higher than the WHO recommendation of up to 5 g daily. The mean dietary salt intake is high in the Indian population, which calls for planning and implementing control of dietary salt consumption measures. [ABSTRACT FROM AUTHOR]

Understanding and evaluating the implications of photovoltaic solar panels (PVSPs) deployment on urban settings, as well as the pessimistic effects of densely populated areas on PVSPs efficiency, is becoming incredibly valuable. Thus, the deployment of low-efficiency, low-cost, and widely available PVSPs may diminish total solar reflectance, raising the risks of PVSPs-based urban heating, particularly during the summertime heatwaves. This study employs and assesses physical parameterizations that account for the impact of PVSPs on Sydney's urban environment in the context of the mesoscale model weather research and forecasting (WRF). To account for the impacts of PVSPs, the parameterization presented in this paper assumes that PVSP arrays are parallel, detachable from roofs, and consist of a single layer. Results showed that increasing PVSPs can raise peak summer ambient temperatures by up to 1.4 °C and surface temperatures by up to 2.3°C at city-scale. Temperature variability was found between the city's eastern and western parts due to the presence of PVSPs. In addition, local warming effects of PVSP were observed at urban district-scale as well. The large-scale deployment of PVSPs at local district-scale of the Sydney during a typical hot day caused air temperature to rise by 1.5 °C during the daytime and decrease by 2.7 °C at nighttime. The patterns of the city's ambient temperature distribution were found to be strongly dependent on synoptic meteorological conditions and advection flow strength. The maximum increases in sensible heat flux and latent heat flux were 245.5 Wm−2 and 11.5 Wm−2, respectively. Wind speed may be raised by up to 1.2 ms−2 due to regional low effect over city domain. As a result, large-scale deployment of PVSPs promotes advective flow between the city and its environs. Modification of the PVSPs in Sydney results in an increase in planetary boundary layer (PBL) heights of up to 537.9 m above the city and may lower pollutant concentrations at ground level. The advent of sea breeze in the city's eastern parts, which reduces the temperature of the coastal zone, along with inland westerly winds, which heat the city's western zones, lessened the intensity of the urban heat island (UHI) phenomenon induced by PVSPs warming. The findings of this study can be used to help policymakers make informed decisions about the use of PVSPs systems. PVSPs with a high solar reflectance in wavelengths that do not convert solar energy to electricity can be considered as an alternative solution to reduce local warming in urban environments. [ABSTRACT FROM AUTHOR]

Electric drones as an autonomous mode of transport are scaling up to transform last-mile goods delivery, raising an urgent need for assessing impacts of drone transport from a systems perspective. In this paper, we conduct systems analyses to assess the environmental, economic, and delivery time impact of large drones for delivery scenarios to pick-up centers between mid-size cities predominantly in rural areas, and deliveries within city limits compared with electric and diesel trucks. Results show that large drones have lower emissions than diesel trucks for deliveries in rural areas and that drones don't compete with electric trucks, mainly due to the high energy demand required for take-off and landing for each delivery. Furthermore, we show that electric drones are an economically more cost-effective option than road-bound transport modes such as diesel and electric trucks due to the high degree of automation, and also provide the fastest delivery times. Our analysis provides unique insights that drones can address rapid electrification and emergency applications due to low costs, high flexibility, and fast operations. However, for regulators and practitioners to realize it as an emission-friendly option it is necessary to determine the optimal size of drones, particularly for use cases in urban areas, avoid very low landings for deliveries, and have home deliveries instead of pick-up points. [ABSTRACT FROM AUTHOR]

This paper developed XJCT-3D, a simulation software for cooling tower wet plume dispersion. By coupling it with the Open GIS component Dotspatial, we have achieved geospatial visual representation of the calculation results, which has solved the problems of low calculation efficiency and insufficient visual representation of the traditional CFD software in the calculation of cooling tower wet plume dispersion. In order to verify the validity of the XJCT-3D software simulation results, we have conducted tracer experimental data from the ChalkPoint power plant. XJCT-3D accurately models wet plume deposition during cooling tower operation. From the XJCT-3D calculation results, we have observed that the maximum value of the cooling tower thermal plume wet deposition occurs near 610 m with a maximum value of 6.9E−07 kg/m2 s. This finding suggests that the cooling tower emissions carry a significant load of particles or droplets that have settled on surfaces at this particular altitude. It provides insights into potential environmental and human health impacts and helps in identifying and assessing areas at relatively higher risk of deposition, such as nearby ecosystems, farmland, or urban areas. This information can contribute to the development of effective mitigation strategies and the implementation of appropriate measures to minimize the impact of cooling tower emissions. [ABSTRACT FROM AUTHOR]

Human mobility is a key driver of infectious disease spread. Recent literature has uncovered a clear pattern underlying the complexity of human mobility in cities: r · f , the product of distance traveled r and frequency of return f per user to a given location, is invariant across space. This paper asks whether the invariant r · f also serves as a driver for epidemic spread, so that the risk associated with human movement can be modeled by a unifying variable r · f . We use two large-scale datasets of individual human mobility to show that there is in fact a simple relation between r and f and both speed and spatial dispersion of disease spread. This discovery could assist in modeling spread of disease and inform travel policies in future epidemics—based not only on travel distance r but also on frequency of return f. [ABSTRACT FROM AUTHOR]

On August 20, 2019, at 2 a.m., a disastrous debris flow occurred in Chediguan gully in Yinxing town, China. The debris flow destroyed the drainage groove and the bridge at the exit of the gully. In addition, the debris flow temporarily blocked the Minjiang River during the flood peak, flooding the Taipingyi hydropower station 200 m upstream and leaving two plant workers missing. To further understand the activity of the debris flow after the Wenchuan earthquake, the characteristics of this debris flow event were studied. Eleven years after the Wenchuan earthquake, a disastrous debris flow still occurred in the Chediguan catchment, causing more severe losses than those of earlier debris flows. In this paper, the formation mechanism and dynamic characteristics of this debris flow event are analysed based on a drone survey, high-definition remote sensing interpretations and other means. The catastrophic debris flow event indicates that debris flows in the Wenchuan earthquake area are still active. A large amount of dredging work in the main gully could effectively reduce the debris flow risk in the gully. In addition, it is also important to repair or rebuild damaged mitigation measures and to establish a real-time monitoring and early warning system for the high-risk gully. [ABSTRACT FROM AUTHOR]

Over the years, the growing availability of extensive datasets about registered patents allowed researchers to get a deeper insight into the drivers of technological innovation. In this work, we investigate how patents' technological contents characterise metropolitan areas' development and how innovation is related to GDP per capita. Exploiting worldwide data from 1980 to 2014, and through network-based techniques that only use information about patents, we identify coherent distinguished groups of metropolitan areas, either clustered in the same geographical area or similar in terms of their economic features. Moreover, we extend the notion of coherent diversification to patent production and show how it is linked to the economic growth of metropolitan areas. Our findings draw a picture in which technological innovation can play a key role in the economic development of urban areas. We contend that the tools introduced in this paper can be used to further explore the interplay between urban growth and technological innovation. [ABSTRACT FROM AUTHOR]

The present paper further develops a coastal vulnerability index formulation (CVI) previously proposed by the authors by integrating a new variable and redefining three variables to improve the suitability of the index for low-lying coasts. Eleven variables are divided into three typological groups: geological, hydro-physical process and vegetation. The geological variables are: geomorphology, shoreline erosion/accretion rates, coastal slope, emerged beach width, and dune. The hydro-physical process group includes: river discharge, sea-level change, mean significant wave height and mean tide range. The vegetation variables are: vegetation behind the back-beach and coverage of Posidonia oceanica. The index was applied to a stretch of the Ionian coast in the province of Crotone in the Calabria region (Southern Italy), and a vulnerability map was produced. A geography information system (GIS) platform was used to better process the data. For the case study area, the most influential variables are shoreline erosion/accretion rates, coastal slope, emerged beach width, dune, vegetation behind the back-beach, and coverage of Posidonia oceanica. The most vulnerable transects are those near urban areas characterized by the absence of dunes and vegetation. Statistical and sensitivity analyses were performed, and the proposed CVI was compared with the previous formulation proposed by the authors and with two other CVI methods present in the literature. [ABSTRACT FROM AUTHOR]

Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions. [ABSTRACT FROM AUTHOR]

China's Green Space System Planning (GSSP) research has gradually expanded from central urban areas to municipal and provincial scales in recent years. Besides, the research on the role of green space in the water environment has also attracted much attention. However, the study of green corridors usually ignored hydrological data, which widespread absence especially in the large area scale. And the scale of green corridor construction mainly focused on central urban areas. This paper took China's Fujian province as an example. Based on the DEM elevation data, the article identified blue corridors without hydrological data. In addition, the green corridors were determined based on the land use data. According to the green corridors and blue corridors protection, we identified the ecological networks and nodes by the network analysis method. The results showed that the blue corridors identified by DEM data were consistent with the hydrological status quo. The regional status of the identified ecological networks and nodes were basically in line with their characteristics, proving the value of the planning methods. Finally, based on the identification results, suggestions for Fujian's ecological networks and nodes are put forward. [ABSTRACT FROM AUTHOR]

Extensive studies have highlighted a need for frequently consistent land cover information for interdisciplinary studies. This paper proposes a comprehensive framework for the automatic production of the first Vietnam-wide annual land use/land cover (LULC) data sets (VLUCDs) from 1990 to 2020, using available remotely sensed and inventory data. Classification accuracies ranged from 85.7 ± 1.3 to 92.0 ± 1.2% with the primary dominant LULC and 77.6 ± 1.2% to 84.7 ± 1.1% with the secondary dominant LULC. This confirmed the potential of the proposed framework for systematically long-term monitoring LULC in Vietnam. Results reveal that despite slight recoveries in 2000 and 2010, the net loss of forests (19,940 km2) mainly transformed to croplands over 30 years. Meanwhile, productive croplands were converted to urban areas, which increased approximately ten times. A threefold increase in aquaculture was a major driver of the wetland loss (1914 km2). The spatial–temporal changes varied, but the most dynamic regions were the western north, the southern centre, and the south. These findings can provide evidence-based information on formulating and implementing coherent land management policies. The explicitly spatio-temporal VLUCDs can be benchmarks for global LULC validation, and utilized for a variety of applications in the research of environmental changes towards the Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

High-quality development paths in important cities are blurry and lacking. In order to explore the important engine for Chengdu high-quality development, driving forces and obstacles recognition has emerged as a pivotal technological solution. Using the Chengdu in Sichuan province of China as a research area and quantitative data from 2010 to 2019, this study has used content mining to recognize urban high-quality development (UHQD) variables, and calculated variables' weights by entropy weight method, and explored driving forces and obstacles of UHQD by the technique for order preference by similarity to ideal solution (TOPSIS) method. The main findings are: (1) there are 36 UHQD variables; (2) Chengdu high-quality development overall level soars from 2017 to 2019, only with two negative growth rates in 2011, 2015; (3) There are 3 key driving force paths: (1) improving green development by volume of industrial wastewater discharged, comprehensively utilised ratio of industrial solid wastes, harmless treatment rate of domestic garbage; (2) stressing open development by total import and export/GDP, actual use of foreign capital, number of foreign tourists/total tourists; and (3) intensifying shared development by funds for urban residents under basic provision protection. (4) 3 clearing obstacles paths can also realize Chengdu high-quality development: (1) improving innovative development level by R&D internal outlay, patent authorisations, state high-level tech enterprises; (2) optimizing coordinated development level by the proportion of tertiary industry; (3) promoting shared development level by urban basic pension insurance. According to these findings, suggestions are put forward to promote Chengdu high-quality development from the perspective of policy implementation. [ABSTRACT FROM AUTHOR]

Urbanization and industrialization have driven rapid socio-economic development, leading to a significant population shift from rural areas to cities. This demographic transition has resulted in substantial changes in rural settlements, presenting considerable challenges for rural revitalization. Given the spatial differentiation, it is crucial to analyze the spatiotemporal evolution patterns and driving mechanisms of rural settlements under various development scenarios and at multiple scales within a county. Such analysis is essential for rational planning and sustainable development. This study analyzes the spatial and temporal evolution patterns and driving mechanisms of rural settlements in Xunwu County, Jiangxi Province, China, using land use dynamics, hot and cold spot analysis, and center of gravity migration models. The Multiscale Geographically Weighted Regression Model (MGWR) is employed to explore their transformation driving mechanisms. The results show that during 2010–2020 in the study area, the total change rate of rural settlements was 39.82%, with a dynamic degree of 2.87%. The average centroid of the settlements is located in Wenfeng Township, gradually migrating southeastward by 3.7 km. Cold spots are shrinking northward, while hotspots are gathering in Chengjiang Town. Socio-economic conditions dominate the evolution of rural clusters in this region, showing obvious spatial heterogeneity. This is followed by locational conditions that are weakening in influence, while the impact of natural geographical conditions exists in the northeast region. The research findings offer a scientifically rigorous and well-founded analysis of the evolution and driving mechanisms of rural settlements. This analysis provides a solid theoretical basis for policy planning in urban-rural integrated development and supports the sustainable growth of rural communities. [ABSTRACT FROM AUTHOR]

Increasing urban density promotes a greater social role for cities. The current low-carbon city development goals put forward higher requirements for carbon performance. Based on the viewpoint of minimizing natural resource input and maximizing value acquisition in ecological benefits, the influence of urban density on spatial carbon performance is analyzed by polynomial function relationship, and Beijing and Shanghai with different urban function positioning are taken as examples for comparative analysis. Combined with Point-of-Interest (POI), the classification benchmark of industrial activities was established, and the spatial kernel density of ArcGIS software was used to analyze the industrial agglomeration characteristics of the two cities. The results show that: 1) The "increase-decrease-increase-decrease" trend of urban spatial carbon performance over time fluctuates around the unary linear trend of urban density.2) Population and building density are too low or too high, which is not conducive to emission reduction. The change of economic density is influenced by the industrial structure. The change of urban density is negatively correlated with the growth rate of spatial carbon performance. In a certain development stage, the increase of urban density will inhibit the growth of spatial carbon performance to some extent. 3) Maintaining the original economic and industrial structure, the increase in economic density brought by the simple expansion of scale is not conducive to emission reduction. The increase of economic density brought by the transformation of economic or industrial structure and the reduction of the proportion of secondary industry is conducive to urban emission reduction. [ABSTRACT FROM AUTHOR]

Climatic, ecological, and socioeconomic factors are facilitating the spread of mosquito-borne diseases, heightening the importance of vector surveillance and control. Citizen science is proving to be an effective tool to track mosquito populations, but methods are needed to detect and account for small scale sampling biases in citizen science surveillance. In this article we combine two types of traditional mosquito surveillance records with data from the Mosquito Alert citizen science system to explore the ways in which the socioeconomic characteristics of urban neighborhoods result in sampling biases in citizen scientists' mosquito reports, while also shaping the spatial distribution of mosquito populations themselves. We use Barcelona, Spain, as an example, and focus on Aedes albopictus, an invasive vector species of concern worldwide. Our results suggest citizen scientists' sampling effort is focused more in Barcelona's lower and middle income census tracts than in its higher income ones, whereas Ae. albopictus populations are concentrated in the city's upper-middle income tracts. High resolution estimates of the spatial distribution of Ae. albopictus risk can be improved by controlling for citizen scientists' sampling effort, making it possible to provide better insights for efficiently targeting control efforts. Our methodology can be replicated in other cities faced with vector mosquitoes to improve public health responses to mosquito-borne diseases, which impose massive burdens on communities worldwide. [ABSTRACT FROM AUTHOR]

Accurate spatial distribution of carbon dioxide (CO2) emissions is essential information needed to peaking emissions and achieving carbon neutral in China. The aim of this study was to map CO2 emissions with high spatial resolution at provincial scale and then explore the scale effect on mapping results. As an example, the spatiotemporal pattern and factors influencing CO2 emissions were examined in Guizhou Province in Western China. With the proposed method, a reasonable spatial distribution of CO2 emissions with high spatial resolution was obtained, which had relatively accurate information on spatial details. The optimal resolution of CO2 emissions at the provincial scale under high spatial resolution was approximately 90 m and 1260 m. More detailed grid data can better reflect the spatial variability of CO2 emissions. Emissions of CO2 were spatially heterogeneous in Guizhou, with high emissions in centers of big cities that gradually spread and decreased from city centers. From 2009 to 2019, the spatial distribution of CO2 emissions developed from agglomeration to dispersion. Areas of high carbon emissions decreased, those of medium carbon emissions increased, and many areas changed from no emissions to carbon emissions. Industrial land had the highest emissions, followed by commercial and transportation lands. Over 10 years, changes occurred in the relation between interregional economic level of Guizhou and CO2 emissions, with the relation changing from linear into an inverted U-shaped relation. The effect of industrial structure on CO2 emissions decreased, and the linear increase between CO2 emissions and the urban scale became more evident. The results of this study will contribute to accurate monitoring and management of carbon emissions in Guizhou, as well as provide support to formulate policies related to controls on carbon emissions in different regions. [ABSTRACT FROM AUTHOR]

In the lower atmosphere, CO2 emissions impact human health and ecosystems, making data at this level essential for addressing carbon-cycle and public-health questions. The atmospheric concentration of CO2 is crucial in urban areas due to its connection with air quality, pollution, and climate change, becoming a pivotal parameter for environmental management and public safety. In volcanic zones, geogenic CO2 profoundly affects the environment, although hydrocarbon combustion is the primary driver of increased atmospheric CO2 and global warming. Distinguishing geogenic from anthropogenic emissions is challenging, especially through air CO2 concentration measurements alone. This study presents survey results on the stable isotope composition of carbon and oxygen in CO2 and airborne CO2 concentration in Naples' urban area, including the Campi Flegrei caldera, a widespread hydrothermal/volcanic zone in the metropolitan area. Over the past 50 years, two major volcanic unrests (1969–72 and 1982–84) were monitored using seismic, deformation, and geochemical data. Since 2005, this area has experienced ongoing unrest, involving the pressurization of the underlying hydrothermal system as a causal factor of the current uplift in the Pozzuoli area and the increased CO2 emissions in the atmosphere. To better understand CO2 emission dynamics and to quantify its volcanic origin a mobile laboratory was used. Results show that CO2 levels in Naples' urban area exceed background atmospheric levels, indicating an anthropogenic origin from fossil fuel combustion. Conversely, in Pozzuoli's urban area, the stable isotope composition reveals a volcanic origin of the airborne CO2. This study emphasizes the importance of monitoring stable isotopes of atmospheric CO2, especially in volcanic areas, contributing valuable insights for environmental and public health management. [ABSTRACT FROM AUTHOR]

The construction models of smart cities and low-carbon cities are crucial for advancing global urbanization, enhancing urban governance, and addressing major urban challenges. Despite significant advancements in smart and low-carbon city research, a consensus on their coupling coordination remains elusive. This study employs mixed-method research, combining qualitative and quantitative analyses, to investigate the coupling coordination between urban smart performance (SCP) and low-carbon level (LCL) across 52 typical smart and low-carbon pilot cities in China. Independent evaluation models for SCP and LCL qualitatively assess the current state of smart and low-carbon city construction. Additionally, an Entropy–TOPSIS–Pearson correlation–Coupling coordination degree (ETPC) analysis model quantitatively examines their relationship. The results reveal that smart city initiatives in China significantly outperform low-carbon city development, with notable disparities in SCP and LCL between eastern, non-resource-based, and central cities versus western, resource-dependent, and peripheral cities. A strong positive correlation exists between urban SCP and overall LCL, with significant correlations in management, society, and economy, and moderate to weak correlations in environmental quality and culture. As SCP levels improve, the coupling coordination degree between the urban SCP and LCL systems also increases, driven primarily by economic, management, and societal factors. Conversely, the subsystems of low-carbon culture and environmental quality show poorer integration. Based on these findings, this study proposes an evaluation system for smart and low-carbon coupling coordination development, outlining pathways for future development from the perspective of urban complex systems. [ABSTRACT FROM AUTHOR]

Based on the panel data of 276 prefecture-level cities in China from 2011 to 2020, this study explores the impact of digital inclusive finance (DIF) on carbon emissions and the intrinsic mechanism of green technological innovation from a spatial perspective by constructing a spatial econometric model, a mediating effect model, and a threshold model. The results show that DIF significantly inhibits carbon emissions, exhibiting a spatial spillover effect. The transmission mechanism from a spatial perspective shows that green technological innovation plays a partial mediating role between DIF and carbon emissions, with the mediating effect accounting for approximately 59.47%. The heterogeneity analysis suggests that the impact of DIF on the reduction of carbon emissions is more pronounced in large and medium-sized cities and eastern regions. Further discussion reveals that the carbon reduction effect of DIF is also influenced by green technological innovation and industrial structure upgrading, showing threshold effects with marginal decreases and gradual increases, respectively. [ABSTRACT FROM AUTHOR]

Yellow River Basin (YRB) is a pivotal region for energy consumption and carbon emissions (CEs) in China, with cities emerging as the main sources of regional CEs. This highlights their critical role in achieving regional sustainable development and China's carbon neutrality. Consequently, there is a pressing need for a detailed exploration of the urban spillover effects and an in-depth analysis of the complex determinants influencing CEs within the YRB. Remote sensing data provide optimal conditions for conducting extensive studies across large geographical areas and extended time periods. This study integrates DMSP/OLS and NPP/VIIRS nighttime light datasets for a longitudinal analysis of urban CEs in the YRB. Using a harmonized dataset from DMSP/OLS and NPP/VIIRS nighttime light from 2007 to 2021, this study quantifies CEs of 58 prefecture-level cities in the YRB. By combining ESDA, STIRPAT model and spatial econometric model, this investigation further clarifies empirically the spatial spillover effects and driving factors of urban CEs. The analysis delineates a phase-wise augmentation in urban CEs, converging towards a distinct spatial distribution characterized by "lower reach > middle reach > upper reach". The spatial autocorrelation tests unravel a complex interplay between agglomeration and differentiation patterns within urban CEs, underscored by pronounced spatial lock-in phenomena. Significantly, this study demonstrates that urbanization, economic development, energy consumption structure, green coverage rate, industrial structure, population, technological progress, and FDI each exhibit varied direct and indirect effect on urban CEs. Furthermore, it elaborates on potential policy implications and future research directions, offering crucial insights for formulating CEs mitigation strategies to advance sustainable development. [ABSTRACT FROM AUTHOR]

Transport accessibility is crucial for defining urban clusters and evaluating a region's centrality and connectivity. To foster equitable growth in urban conglomerates, it is crucial to understand the relationship between transport accessibility and regional development. This study introduces the concept of 'regional efficiency'—the effectiveness of converting regional inputs into outputs—determined via the super-efficiency Data Envelopment Analysis methodology, to assess the progression of regional development. Employing a combination of bivariate spatial autocorrelation and spatial regression analysis, this research elucidates the spatial dynamics between transport accessibility and regional efficiency, both at macro and micro levels. A binary Logit model identifies the factors affecting the Moran's I correlation between regional efficiency and transport accessibility. Based on the diverse urban characteristics within a single conglomerate, tailored development strategies are suggested. Focusing on the Yangtze River Delta Urban Agglomeration in China as a case study, four distinct spatial clusters—High–High (HH), Low–Low (LL), High–Low (HL), and Low–High (LH)—are identified, based on the local correlation between regional efficiency and transport accessibility. The findings reveal that regions with a High–High Moran's I correlation between road accessibility and regional efficiency predominantly located in the eastern sectors of the Yangtze River Delta, exhibiting effective regional efficiency. These regions are characterized by superior road accessibility, aligning well with their regional efficiency metrics. For air accessibility, cities classified under the HH category, including Shanghai and its neighboring cities, demonstrate a significant spatial correlation with regional efficiency. Population density and urban tier are key predictors of the significance of the Moran's I correlation between road accessibility and regional efficiency. In contrast, for air accessibility, these factors assume an inverse role. The identified cluster types (HH, LL, LH, and HL) are proposed as predictive indicators for the significance of the Moran's I relationship between air accessibility and regional efficiency. [ABSTRACT FROM AUTHOR]

As cities continue to grow globally, characterizing the built environment is essential to understanding human populations, projecting energy usage, monitoring urban heat island impacts, preventing environmental degradation, and planning for urban development. Buildings are a key component of the built environment and there is currently a lack of data on building height at the global level. Current methodologies for developing building height models that utilize remote sensing are limited in scale due to the high cost of data acquisition. Other approaches that leverage 2D features are restricted based on the volume of ancillary data necessary to infer height. Here, we find, through a series of experiments covering 74.55 million buildings from the United States, France, and Germany, it is possible, with 95% accuracy, to infer building height within 3 m of the true height using footprint morphology data. Our results show that leveraging individual building footprints can lead to accurate building height predictions while not requiring ancillary data, thus making this method applicable wherever building footprints are available. The finding that it is possible to infer building height from footprint data alone provides researchers a new method to leverage in relation to various applications. [ABSTRACT FROM AUTHOR]

With advancements in sustainable urban development, research on urban functional areas has garnered significant attention. In recent years, Point-of-Interest, with their large volume of information and ease of acquisition, have been widely applied in research on urban functional domains. However, scholars currently focus on the identification of urban functional areas, usually relying on data from a single period, whereas research on the prediction of functional areas has not yet been well validated. Therefore, in this study, we propose a new method based on several years of POI data to predict urban functional areas. Taking Nanjing City, Jiangsu Province, as an example, we first identified the functional area distribution of the old city of Nanjing over several years using POI data and then designed multiple sets of experiments to explore the CA–Markov model's ability to predict functional areas from various aspects, including model overall accuracy, robustness, and comparison analysis between predictions and actual situations. The results show that (1) for mixed or single functional areas, the model's predictions over several years tend to be stable, and the accuracy of the predictions over many years indicates the robustness of the model in predicting urban functional areas. (2) For mixed functional areas in cities, model predictions largely rely on the distribution of the base years used for prediction, leading to inaccurate results; thus, it is still not applicable for simulating and predicting mixed functional areas. (3) For single functional areas in cities or primary functions within an area, the model's predicted degree of change was close to the actual degree of change, making the results referable. [ABSTRACT FROM AUTHOR]

The enhancement of regional comprehensive development ability is significantly impacted by the study on the implementation effect of regional integration strategies. The integration strategy's impact on urban development during COVID-19 in the Yangtze River Delta(YRD) is unclear. According to prior industrial transfer theory, Hefei, Anhui's capital, is difficult to transfer industries, and other YRD cities push industry integration in Anhui. This study employs the theory of economic and land resource use to examine the resilience of the industrial economy during an epidemic by using industrial land as a representation of industrial economic development. The three cities in Anhui—Wuhu, Maanshan, and Chuzhou (Wu-ma-Chu) were selected as the research area. The study employed the UNet deep learning method to detect the land use types in Wu-ma-Chu. The land transfer matrix and the standard deviation ellipse were utilised to research the alterations in industrial land use and the spatial distribution of industrial output value, respectively. The results showed that the industrial land in Machu continued to grow during the outbreak, highlighting the resilience of the region's industrial economy. During 2019–2022, the elliptical ring of industrial output value is distributed in Nanjing, revealing the radiating role of Nanjing in integrating into the integration of the YRD. This confirms China's YRD integration strategy, strengthens regional economic resilience, and encourages coordinated regional economic development. [ABSTRACT FROM AUTHOR]

Due to the increasing importance of exposome in environmental epidemiology, feasibility and usefulness of an Environmental Data Management System (EDMS) using Open Data was evaluated. The EDMS includes data from 10 European cities (Celje (Slovenia), Łódź (Poland), Manchester (UK), Palermo (Italy), Paris (France), Porto (Portugal), Regensburg (Germany), Reus (Spain), Rijeka (Croatia), Thessaloniki (Greece)) about external non-specific and specific exposome factors at the city or country level (2017–2020). Findings showed that the highest values of life expectancy were in Reus females (86 years) and Palermo males (81 years). UK had the highest obesity rate (28%), Croatia the highest prescribed drug consumption (62%), Greece and Portugal the highest smoking rates (37%, 42%) and daily alcohol consumption (21%), respectively. The most polluted cities were Thessaloniki for PM10 (38 µg/m3), Łódź for PM2.5 (25 µg/m3), Porto for NO2 (62 µg/m3) and Rijeka for O3 (92 µg/m3). Thessaloniki had the highest grey space (98%) and Łódź the highest cumulative amount of pollen (39,041 p/m3). The highest daily noise levels ≥ 55 dB was in Reus (81% to traffic) and Regensburg (21% to railway). In drinking water, arsenic had the highest value in Thessaloniki (6.4 µg/L), boron in Celje (24 mg/L) and lead in Paris (46.7 µg/L). Portugal and Greece showed the highest pesticide residues in food (7%). In conclusion, utilizing open-access databases enables the translation of research findings into actionable strategies for public health interventions. [ABSTRACT FROM AUTHOR]

Currently, a combination of natural and human factors has led to the lack of cost-effective production, resulting in the downturn of traditional animal husbandry (DTLH) in rural regions. This research aims to investigate the factors contributing to the DTLH in indigenous communities in northwestern Iran. The statistical population consisted of pastoralists residing in the villages of Namin-Ardabil, Iran. The research method employed was descriptive-analytical, and a questionnaire was used as the data collection tool. The sample size was determined by selecting approximately 5–10% of households in each village, preferably the household head. Friedman's test was utilized to prioritize the most significant factors influencing DTLH. The findings reveals that the most crucial economic criteria contributing to the DTLH were "the high cost of providing inputs and fodder required for livestock (mean rank = 11.12)," "more economic opportunities and access to well-paying employment opportunities in the city (mean rank = 8.99)", and "low profit from livestock farming in the rangeland (mean rank = 10.60)". Moreover, the most important social criteria were "uncertainty regarding the future well-being of children and the social and economic situation in the village (mean rank = 14.12)", "motivation for academic and career development in urban areas (mean rank = 14.10)", and "access to specialized and professional training opportunities in cities (mean rank = 13.80)". Furthermore, the most crucial ecological criteria impacting the DTLH were "drought" (mean ran = 7.96)" and "non-implementation of range management plans and grazing permits" (mean rank = 6.07)". In general, the results indicated that the ecological criteria had the highest impact on the DTLH, followed by social and economic criteria, with values of 41.1%, 34.6%, and 24.29%, respectively. Overall, understanding the challenges faced by traditional livestock husbandry and identifying the factors contributing to its decline is crucial for developing effective strategies to support and sustain this industry in rural areas. [ABSTRACT FROM AUTHOR]