Search

The transport sector is crucial in influencing anthropogenic pollution. By employing Chinese prefecture-level city data from 2003 to 2019 and a sample of 443124 observations of industrial firms from 2003 to 2013, this paper treats the opening of high-speed rail (HSR) as a quasi-natural experiment and uses a multi-period difference-in-differences (DID) method to investigate the impact of HSR on haze pollution. The findings reveal that (1) HSR has a significant negative effect on cities' PM 2.5 concentrations, and the result is held after a series of robustness checks; (2) the analysis based on Chinese industrial firm data also yields significant results in reducing smoke and dust emissions by HSR, providing micro-level understanding for the main conclusion; (3) at the firm level, heterogeneity derives from firm ownership, location, and industry; (4) the reduction in industrial firms' labor and capital distortion and resource misallocation play a crucial role in the HSR's impact on mitigating haze pollution; (5) at the city level, HSR reduces haze pollution by improving overall resource allocation across cities, and promoting the flow of capital to cities that are more developed and have higher returns. These results indicate that recognizing the causal relationship between HSR and haze pollution and the impact mechanism poses policy implications for inter-city transportation infrastructure development and pollution control. • We provide empirical evidence from both macro and micro perspectives that HSR can reduces haze pollution. • The heterogeneity effects at the firm level come from firm ownership, location, and industry. • Resource allocation effect is found to be an important channel for HSR on haze pollution. • The findings provide implications for HSR, market integration and haze pollution control. [ABSTRACT FROM AUTHOR]

The extensive high-speed rail (HSR) network in China has significantly enhanced regional population mobility, yet its impact on the well-being of migrant workers remains underexplored. Utilizing data from the China Migrant Dynamic Survey (CMDS) from 2014 to 2018, this study investigates the influence of HSR on wage premiums for migrant workers and identifies the factors driving these premiums using the non-parametric nearest neighbor matching method. The findings reveal that HSR confers a significant wage premium of 13.1% for migrant workers in cities with HSR infrastructure compared to cities without it. This wage premium effect is particularly pronounced in less developed western China and in cities with larger populations and a higher proportion of tertiary sector economy. The study finds a 10.54% increase in wage premiums for intra-province migrant workers due to HSR, while the effect remains negligible for inter-province migrant workers. Moreover, the wage premium effect is stronger for higher-skilled labor and for migrant workers aged 16 to 45. It is particularly significant for professionals, administrative staff, and workers in the service industry. The HSR wage premium effect is multifaceted, exhibiting both level and growth effects, with the latter intensifying over time after HSR introduction. Overall, the findings suggest that HSR deployment positively influences migrant worker wages by enhancing travel convenience, improving market access, fostering knowledge spillovers, and facilitating industry transfers. However, these impacts vary by location, skill level, and industry. • The study reveals a 13.1% wage premium for migrant workers in cities with HSR infrastructure. • HSR's wage premium effect is the strongest in western China, larger cities, and those with a higher tertiary sector economy. • Intra-province migrants gain a 10.54% wage premium from HSR; inter-province workers see minimal effects. • Higher-skilled labor and workers aged 16-45 benefit most, especially in professional and service roles. • HSR's impact on wages grows over time, driven by better travel, market access, knowledge spillovers, and industry shifts. [ABSTRACT FROM AUTHOR]

• Heterogeneity in pedestrians' perceived importance of crossing facilities was studied. • TOPSIS was used to derive the relative importance and ranking of attributes. • Heterogeneity in perceived importance was investigated using non-parametric tests. • Mann-Whitney U and Kruskal-Wallis H tests were employed as non-parametric tests. • Heterogeneity was found to be significant w.r.t walking preference and age group. • There was no effect of gender on heterogeneity in perceived importance. Although several studies in the past discussed the effects of socio-demographic and trip characteristics on users' preferences towards crossing facilities in urban areas, they were mostly confined to metro cities or million-plus cities. Adequate investigation has not been performed for the same in the small-sized cities where pedestrian activities are expected to be more frequent because of the higher share of shorter and walkable trip lengths. Accordingly, the present study aimed to investigate the heterogeneity in the perceived importance of crossing facility attributes among different pedestrian groups based on gender, age group, and walking preference. The study was conducted in a small-sized city, Roorkee, in the state of Uttarakhand, India. A face-to-face questionnaire survey of 554 pedestrians was conducted to collect their perceived importance towards 12 crossing facility attributes under study using a 5-point Likert-type ordinal scale. Collected data was analyzed using the non-parametric tests to measure the heterogeneity in the perceived importance of crossing facility attributes among aforementioned pedestrian groups. Subsequently, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method was used to derive relative importance scores of attributes found statistically significant in heterogeneity tests for different pedestrian groups. The findings of the present study reveal that perceived importance towards crossing facility attributes is heterogeneous based on the pedestrians' age group and walking preferences; however, it remains unaffected by gender. These findings would help policymakers, planners, and government authorities frame improvement strategies for the existing crossing facilities in the city. [ABSTRACT FROM AUTHOR]

Transcritical CO 2 system is eco-friendly for the application of refrigeration and cooling in supermarket. To evaluate the applicability of transcritical CO 2 supermarket refrigeration system in China with different climate regions, this study focuses on the field tests of a transcritical CO 2 two-stage throttling system in a supermarket in Suzhou, Jiangsu Province, China. Furthermore, based on the tested data, the system energy and emissions performance models of four system configurations are also developed and validated, including the system integrated with an internal heat exchanger, a parallel compression, and mechanically assisted subcooling. In order to improve the usability of the system in different climatic zones, 40 cities were selected for calculation in China. Five representative cities (Beijing, Harbin, Xiamen, Chongqing, and Kunming) located in different climate regions of China are selected, and the annual performance factor and life cycle climate performance (LCCP) are determined to evaluate the application potential of the CO 2 refrigeration systems in different climate conditions. The tested results show the operation mode of transcritical and subcritical changes occurs at an ambient temperature of about 27 °C, at which the coefficient of performance (COP), compressor discharge pressure and discharge temperature change dramatically. The simulation results demonstrate that the mechanical subcooling system shows the best performance. The annual performance factor can be improved by 18.69 % when the mechanical subcooling is adopted. For the case of the system used in Xiamen by using mechanical subcooling, the carbon emissions can be reduced by 19.3 %. [ABSTRACT FROM AUTHOR]

• The CE-TCP relationship is nonlinear globally, with CE exhibiting an initial sharp decline followed by a gradual reduction as TCP rises. • The nonlinear CE-TCP relationship is more pronounced in tropical and arid climates compared to other regions. • There is a higher CE and cooling potential of mitigating urban population heat exposure in areas with fewer trees. Investigating the relationship between cooling efficiency (CE) and tree cover percentage (TCP) is critical for planning of green space within cities. However, the spatiotemporal complexities of the intra-city CE-TCP relationship worldwide with distinct climates, as well as the differing impacts of consistently increasing tree cover within urban regions on cooling potential, remain unclear. Here we used satellite-derived MODIS observations to investigate the CE-TCP relationship across 440 global cities during summertime from 2018 to 2020. We further investigated the impacts of enhancing tree cover by a consistent amount in different urban locales on the reduction of population heat exposure among specific age groups. Our results demonstrate a nonlinear CE-TCP relationship globally – CE exhibits an initial sharp decline followed by a gradual reduction as TCP rises, and this nonlinearity is more pronounced in tropical and arid climates than in other climate zones. We observe that 91.4% of cities experience a greater reduction in population heat exposure when introducing the same amount of TCP in areas with fewer trees than in those with denser canopies; and heat exposure mitigation is more prominent for laborers than for vulnerable groups. These insights are critical for developing strategies to minimize urban heat-related health risks. [ABSTRACT FROM AUTHOR]

Most cities around the world are experiencing rapid expansion and urbanization as a result of increasing industrial activity and construction while reducing green space availability which impacts our thermal environment. The variation of both the land cover distribution and the air pollutant concentration impacts the LST pattern in different cities. Thus, the present study investigates the relation of Land Surface temperature (LST) with each land cover parameters such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Apparent Thermal Inertia (ATI), artificial sensible heat flux (Has) and air pollutants such as Carbon monoxide (CO), Nitrogen dioxide (NO 2), Sulphur Dioxide (SO 2), ozone (O 3)) in four different cities in India using satellite data. The correlation of LST with NDVI and ATI were found negative whereas with NDBI and Has were found positive in the four cities. The impact of each air pollutant on LST was found to vary with cities. Further, the combined influence of all the parameters on LST was analysed using ANOVA test and percentage contribution of each parameter towards LST was determined. The combined percentage contribution of land surface parameters such as NDVI, NDBI and ATI were found to be 97.8, 98.0, 74.4 and 84.4 for Bangalore, Bikaner, Ahmedabad and Varanasi, respectively. The combined percentage contribution of air pollutants such as CO, NO 2 , SO 2 and O 3 was found to be 1.3, 1.9, 2.9 and 12.9 for Bangalore, Bikaner, Ahmedabad and Varanasi, respectively. Therefore, the present study reveals that the land cover distribution had greater influence on LST than air pollutants in different cities. [ABSTRACT FROM AUTHOR]

• Understanding plastic litter in cities is crucial to preventing marine pollution. • Citizen science is suitable for long-term, extensive data collection. • Despite human error, ∼30 % of data could be used to visualize and quantify litter. • Litter in cities was studied using Pirika and deep learning-based image processing. • Trained models exhibited high precision and recall in classifying litter types. Cities are a major source of litter pollution. Determination of the abundance and composition of plastic litter in cities is imperative for effective pollution management, environmental protection, and sustainable urban development. Therefore, here, a multidisciplinary approach to quantify and classify the abundance of litter in urban environments is proposed. In the present study, litter data collection was integrated via the Pirika smartphone application and conducted image analysis based on deep learning. Pirika was launched in May 2018 and, to date, has collected approximately one million images. Visual classification revealed that the most common types of litter were cans, plastic bags, plastic bottles, cigarette butts, cigarette boxes, and sanitary masks, in that order. The top six categories accounted for approximately 80 % of the total, whereas the top three categories accounted for more than 60 % of the total imaged litter. A deep-learning image processing algorithm was developed to automatically identify the top six litter categories. Both precision and recall derived from the model were higher than 75 %, enabling proper litter categorization. The quantity of litter derived from automated image processing was also plotted on a map using location data acquired concurrently with the images by the smartphone application. Conclusively, this study demonstrates that citizen science supported by smartphone applications and deep learning-based image processing can enable the visualization, quantification, and characterization of street litter in cities. [ABSTRACT FROM AUTHOR]

Transportation is a key barrier for accessing healthcare services. This is particularly concerning for the millions suffering from opioid use disorder (OUD) since treatment for OUD can require in-person visits daily or a few times a week. To better understand how public transit influences access to treatment for OUD, we observe distances among opioid treatment programs (OTPs), buprenorphine providers, and public transit stops in the U.S. We also investigate the possible role of micromoblity, specifically bikesharing and e-scooters, in filling these transportation gaps. Results show that in urban counties, 48–91% of buprenorphine providers and OTPs are within possible walking distance (i.e., 0.4–1.4 km) of public transit stops, suggesting a high degree of heterogeneity in public transit access even among urban counties. In rural counties, only 5–40% of buprenorphine providers and OTPs are within possible walking distance of public transit stops. Given that many micromobility programs are in urban areas, they could complement public transit in urban counties where public transit runs less frequently, but not in rural counties. We also find that, on average, the odds an OTP or a buprenorphine provider is within walking distance of a public transit stop decreases outside the large central metro counties, as well as in counties that have a greater percentage of people with lower educational attainment. Affordable transportation options will continue to limit treatment options for people suffering from OUD, especially outside major metropolitan areas, unless public transit or other transportation innovations are expanded or telemedicine becomes more accessible. • Transportation is a barrier for accessing treatment for opioid use disorder. • We study the distance between public transit stops and treatment providers. • Outside major metro areas, treatment is hard to access using only public transit. • There is heterogeneity in access even among urban counties. • Lower educational attainment is associated with more difficult access. [ABSTRACT FROM AUTHOR]

Electric mobility hubs (eHUBS) represent an innovative approach to providing diverse shared electric transportation options, aimed at curbing private car use, and mitigating associated environmental impacts. Assessing the impact of eHUBS on travel choices across different cities requires significant resource and time investment due to the need for localized data collection and model development. This paper proposes a potential solution to this challenge by investigating the transferability of mode choice models originally developed for eHUBS in Amsterdam to predict behaviour towards eHUBS in Manchester. Multinomial Logit (MNL) and mixed logit models were transferred using four different procedures, and their effectiveness was evaluated using three assessment measures. The findings indicate that a scaled mixed logit model with an updated Alternative Specific Constant (ASC) outperforms other models in terms of its transfer effectiveness, both for disaggregate and aggregate assessment measures. The interplay between transfer procedures and assessment measures also was examined, with results indicating enhancements in disaggregate transferability measures with the 'scaling' transfer procedure, while 'updating the Alternative Specific Constants (ASCs)' improved predictions of aggregate mode shares. Following the analysis, the paper presents an in-depth discussion to provide a nuanced understanding of transferability and thus offers valuable insights for researchers planning future studies and practical considerations for policymakers. • The paper examines spatial transferability of mode choice models between eHUBS cities. • Model scaling resulted in improvement of disaggregate measures of transferability. • Updating ASC improves aggregate mode share predictions of transferred model. • Scaled mixed logit model with updated ASC explain 75% of overall behaviour. • Transferability of mixed logit model gives better results as compared to MNL model. [ABSTRACT FROM AUTHOR]

In the path version of the Travelling Salesman Problem (Path-TSP), a salesman is looking for the shortest Hamiltonian path through a set of n cities. The salesman has to start his journey at a given city s , visit every city exactly once, and finally end his trip at another given city t. In this paper we show that a special case of the Path-TSP with a Demidenko distance matrix is solvable in polynomial time. Demidenko distance matrices fulfill a particular condition abstracted from the convex Euclidian special case by Demidenko (1979) as an extension of an earlier work of Kalmanson (1975). We identify a number of crucial combinatorial properties of the optimal solution and design a dynamic programming approach with time complexity O (n 6). [ABSTRACT FROM AUTHOR]

• Bulk cold stores are key in the perishable produce cold handling chain. • The 16 cities had cold storage capacity of 4.5 m3 per 1000 inhabitants. • Temperature varied significantly from set points in all the cold stores. • Majority (90.3% by volume) of the cold stores were privately owned. Investment in the food cold chain has been reportedly identified as a solution to extensive postharvest losses worldwide. However, cold chain investment in the Ugandan food value chain is largely unknown. This study located, characterised, and determined the efficacy of bulk cold storage facilities used in handling perishable agricultural food produce in the 16 city districts of Uganda. Only 9/16 city districts had bulk cold storage facilities, translating to a cold storage capacity of 4.5 m3 per 1,000 inhabitants. The private sector owned the highest proportion by volume (90.3%) of these facilities with the highest volume used for handling multiple perishable products (11,590 m3). Generally, temperature varied significantly from the respective set points in the facilities. Variations were observed for between 1/3 to 3/4 of the logged period above maximum allowable storage temperatures for the different products, showing efficacy lapses. These results indicate investment and management gaps and opportunities in this indelible sector in food value chain by both government and private sector players. [ABSTRACT FROM AUTHOR]

Do young politicians prioritize other types of municipal spending than old politicians? We study this question using hand-collected candidate-level data on municipal elections (1996–2020), along with detailed administrative data on municipal spending in Bavaria. Our identification strategy makes use of within-party candidate-level races for marginal seats. Our findings indicate that municipalities with a higher proportion of young councilors allocate more resources to social spending. Further analysis reveals that this social spending increase is primarily driven by the expansion of public child care. Exploring mechanisms, we find evidence suggesting that young councilors affect policy choices indirectly through between- and within-party bargaining. [ABSTRACT FROM AUTHOR]

This paper examines the influence of economic policy uncertainty (EPU) on foreign direct investment (FDI). By utilizing a comprehensive dataset spanning 264 Chinese cities from 2005 to 2014, we uncover a negative relationship between EPU and FDI inflows. In addition, through heterogeneity tests, we demonstrate that this effect is more pronounced in cities characterized by a higher degree of marketization, stronger financial development, and a larger proportion of industrial production. Moreover, we observe that FDI exhibits greater sensitivity to EPU fluctuations following the 2008 Global Financial Crisis. To provide an explanation for these findings, we propose an open-economy model incorporating uncertainty. • We show the negative impact of rising EPU on FDI. • We use the data on province-level EPU and city-level FDI. • FDI is more sensitive to EPU in better developed cities. [ABSTRACT FROM AUTHOR]

• This paper identified the innovation networks and innovation environment as the core components of the regional innovation system. • A two-region, three-sector New Economic Geography model is developed by integrating the digital economy, innovation cooperation, R&D elements flow, and innovation output into a unified framework. • Digital economy promotes innovation output through promoting intra-regional and inter-regional cooperation and attracting the flow of R&D elements personnel and capital. • Underdeveloped cities benefit more from digital economy, while large central cities function as conduits and generate spillover effects to interconnected regions. This paper explored the paradigm shift in spatial innovation dynamics driven by the rapid emergence of the digital economy (DIGE) through the lens of the regional innovation system (RIS). By integrating DIGE, RIS, and innovation output into a unified analytical framework, this study examined the impact and mechanisms of DIGE on innovation output across 330 Chinese cities from 2011 to 2020. Results show that DIGE development significantly contributes to innovation output. This contribution is mediated by DIGE's strengthening of the RIS, primarily through its facilitation of integration into innovation networks and enhancement of the innovation environment. Regional heterogeneities are evident in the innovation-promoting influence of DIGE, with less developed cities, cities with underdeveloped infrastructure, and smaller cities benefiting more significantly. While the direct impact of DIGE on large central cities is subtle, their pivotal positions enable them to radiate and disseminate innovation spillovers to connected cities through extensive cooperative networks. This study underscored the potential of leveraging DIGE, especially in disadvantaged regions, to cultivate robust and synergistic RIS and act as catalysts for augmented innovation output. [Display omitted] [ABSTRACT FROM AUTHOR]

Novel view synthesis (NVS) of urban scenes enables the exploration of cities virtually and interactively, which can further be used for urban planning, navigation, digital tourism, etc. However, many current NVS methods require a large amount of images from known views as input and are sensitive to intrinsic and extrinsic camera parameters. In this paper, we propose a new unified framework for NVS of urban scenes with fewer required views via the integration of scene priors and the joint optimization of camera parameters under an geometric constraint along with NeRF weights. The integration of scene priors makes full use of the priors from the neighbor reference views to reduce the number of required known views. The joint optimization can correct the errors in camera parameters, which are usually derived from algorithms like Structure-from-Motion (SfM), and then further improves the quality of the generated novel views. Experiments show that our method achieves about 25. 375 dB and 25. 512 dB in average in terms of peak signal-to-noise (PSNR) on synthetic and real data, respectively. It outperforms popular state-of-the-art methods (i.e., BungeeNeRF and MegaNeRF) by about 2– 4 dB in PSNR. Notably, our method achieves better or competitive results than the baseline method with only one third of the known view images required for the baseline. The code and dataset are available at https://github.com/Dongber/PriNeRF. [ABSTRACT FROM AUTHOR]

Street view imagery (SVI) is instrumental for sensing urban environments, benefitting numerous domains such as urban morphology, health, greenery, and accessibility. Billions of images worldwide have been made available by commercial services such as Google Street View and crowdsourcing services such as Mapillary and KartaView where anyone from anywhere can upload imagery while moving. However, while the data tend to be plentiful, have high coverage and quality, and are used to derive rich insights, they remain simple and limited in metadata as characteristics such as weather, quality, and lighting conditions remain unknown, making it difficult to evaluate the suitability of the images for specific analyses. We introduce Global Streetscapes — a dataset of 10 million crowdsourced and free-to-use SVIs sampled from 688 cities across 210 countries and territories, enriched with more than 300 camera, geographical, temporal, contextual, semantic, and perceptual attributes. The cities included are well balanced and diverse, and are home to about 10% of the world's population. Deep learning models are trained on a subset of manually labelled images for eight visual-contextual attributes pertaining to the usability of SVI — panoramic status, lighting condition, view direction, weather, platform, quality, presence of glare and reflections, achieving accuracy ranging from 68.3% to 99.9%, and used to automatically label the entire dataset. Thanks to its scale and pre-computed standard semantic information, the data can be readily used to benefit existing use cases and to unlock new applications, including multi-city comparative studies and longitudinal analyses, as affirmed by a couple of use cases in the paper. Moreover, the automated processes and open-source code facilitate the expansion and updates of the dataset and encourage users to create their own datasets. With the rich manual annotations, some of which are provided for the first time, and diverse conditions present in the images, the dataset also facilitates assessing the heterogeneous properties of crowdsourced SVIs and provides a benchmark for evaluating future computer vision models. We make the Global Streetscapes dataset and the code to reproduce and use it publicly available in https://github.com/ualsg/global-streetscapes. [Display omitted] • Largest labelled dataset, with 346 attributes that characterise street photos. • Baseline models and ground truth labels for benchmarking computer vision models. • Reproducible framework to sample and enrich SVIs from cities all around the world. • In-depth discussion of how the dataset could drive novel research questions. • Taking forward the work of Mapillary and KartaView, and their contributors. [ABSTRACT FROM AUTHOR]

There is an ongoing process that greenhouse gas emissions of transport will be incorporated in the European Emissions Trading System. The cap-and-trade approach will result in substantial price increases for fossil fuels which will affect affordability of the transport systems. Within this paper the regressive effect on car-owning households is described in different area categories of the urban and rural region in Germany. Equal-per-household redistribution of the carbon revenue could reverse the regressive effect into a progressive effect. However, there is substantial variation within the different economic status groups leaving notable shares of households with a very low economic status without a positive net transfer. This share will be lowest in the metropolises of the urban region and highest in small-sized cities/village areas of the urban and rural region. Particularly in the latter area categories, these households may need temporary mobility allowances due to limited abatement options. Despite the environmental bonus, electric car-owning households still belong to groups of higher economic status, and public transport supply is limited, particularly in the small-sized cities/village areas of the urban and rural region. • The financial burden of transport carbon pricing varies by the economic status of households. • Within all economic status groups, the financial burden varies also by area categories. • Equal-per-household-payments could turn the regressive effect of carbon pricing progressive. • Yet some households with a very low economic status may still need temporary mobility allowances. [ABSTRACT FROM AUTHOR]

In this paper, we develop the concept of a "Sustainable Mobility Guarantee". We first review existing "Mobility Guarantees", which are rather motivated by socioeconomic interests than environmental sustainability and classify them. Based on this assessment, we define a Sustainable Mobility Guarantee, which extends existing approaches with environmental interests. It is an emerging concept in policymaking to ensure a certain level of mobility without the need for private cars - particularly in rural areas - but it is still in its infancy and lacks clear definitions. The concept embraces the idea of Classical Mobility Guarantees while seeking to enable and promote the use of non-automobile modes for everyday travels for everyone, not only for specific trip purposes like commuting, nor for specific target groups like the elderly. We then discuss the practical implementation and financial feasibility. Implementation is possible through programmatic or regulatory approaches, which may serve as a potential transitional basis for legal regulation. At least in developed countries, implementing mobility services realizing a Sustainable Mobility Guarantee is deemed financeable, given that financial instruments now subsidizing automobile use are shifted towards implementation of the guarantee, without being detrimental to the economy. • Policy, laws and regulations to guarantee human mobility are reviewed and classified from several perspectives. • A Classical Mobility Guarantee aims to provide fallback for people without car or ability to drive. • A Sustainable Mobility Guarantee aims to motivate people to shift away from cars both in cities and rural areas. • The concept for a Sustainable Mobility Guarantee is developed and transition is discussed. • An analysis of implementation cost is estimated and discussed using Austria as a case study. [ABSTRACT FROM AUTHOR]

This research examines the use of Shared Autonomous Electric Vehicles (SAEVs) in 374 U.S. small and medium-sized urban areas, focusing on fleet and infrastructure needs through agent-based simulations. It assesses metrics such as fleet size, trips per vehicle, and charging station requirements, considering two charger types: Level 2 and Level 3. The findings show significant spatial differences in SAEV operations and infrastructure across these cities. Statistical analysis links these variations to regional road networks and travel patterns. The study finds Level 3 chargers more efficient, requiring fewer stations and enabling more trips per vehicle compared to Level 2 chargers. Furthermore, Level 3 chargers exhibit a greater number of trips per SAEV and a higher ratio of vehicles to charging stations. These findings highlight the significance of considering charging infrastructure characteristics to optimize SAEV fleet performance and promote sustainable transportation systems in urban areas. This study significantly contributes by identifying the spatial variation and correlates of the SAEVs' operational and charging infrastructural performance. Policymakers, urban planners, and transportation service providers can leverage these insights to design and implement effective charging infrastructure for SAEV fleets, thereby advancing the transition to cleaner and more efficient mobility solutions. • This study investigates the potential of Shared Autonomous Electric Vehicles (SAEVs). • Agent-based simulations examined critical metrics such as fleet size and charging station needs. • The analysis includes two types of charging stations, Level 2 and Level 3. • Notable spatial variations in SAEV fleet and charging infrastructure performance are identified. • Regional road network characteristics and travel demand patterns contribute to spatial variations. [ABSTRACT FROM AUTHOR]

Local authorities have a strategic role in mitigating the environmental impacts of the transport sector. However, they struggle to integrate environmental issues into their decision-making processes, especially planning. In the European context of the Sustainable Urban Mobility Plan approach and Strategic Environmental Assessments (SEAs), this paper scrutinises three French localities to determine the current best practices and limitations for designing mobility plans and integrating environmental issues. Several limitations are identified: (1) limited expertise in defining and characterising actions and objectives, which complexifies plans' design, understanding, and monitoring; (2) a lack of a framework to conduct long-term quantitative environmental assessments and to use the results to influence decision effectively; and (3) monitoring processes are barely described in the documents, and the planning horizon where objectives are defined is not in sync with the indicators' mandatory evaluation period. This French case study thus reveals that European planning practices must be further analysed and improved to deal with the rising environmental concerns, e.g. through an operational framework to design mobility plans with effective integration of environmental issues. • Planning supports local authorities in moving towards a more sustainable mobility. • There is no robust approach to defining and characterising actions and objectives. • Robust long-term quantitative assessments are lacking to support planning. • Monitoring modalities are scarcely described in plans and SEAs. • Improving planning frameworks would help the integration of environmental issues. [ABSTRACT FROM AUTHOR]

In the context of a global economic slowdown and structural shifts, comprehending labor market stability is crucial for devising effective macro-employment strategies. This research introduces an innovative framework to analyze employment resilience in the wake of China's smart city pilot policy. Utilizing data from 275 prefecture-level cities across China, spanning 2008 to 2020, the study delves into the beneficial effects of the smart city pilot policy on employment resilience. It employs a dual approach, integrating the Differences-in-Differences method (DID) with robustness analysis. Findings indicate that employment resilience in smart city pilot cities is approximately 0.58% higher compared to non-pilot cities. Factors such as location, size, and city type exhibit varying influences on this outcome. The research further reveals that entrepreneurial activities significantly mediate the link between smart city policies and employment resilience. Additionally, the concentration of manufacturing and productive services, along with their interplay, demonstrates notable moderating effects. This investigation broadens the economic research scope regarding smart cities and offers fresh empirical insights into the labor market impacts of smart city pilot policies, serving as a valuable guide for policymakers in managing employment markets. [ABSTRACT FROM AUTHOR]

Climate change poses an enormous global challenge, particularly for human economic activities. Previous literature has paid limited attention to the impact of temperature change on domestic trade. To examine the nexus between temperature and domestic trade, we employ panel data from 285 Chinese cities from 2000 to 2021 and a spatial econometric model. First, we reveal significant spatial correlation between domestic trade between cities. More importantly, a city's domestic trade is found to be significantly influenced by temperature changes in neighbouring cities. Specifically, the significantly negative spillover effect of temperature changes on domestic trade is consistent with the significantly negative direct effect, suggesting an overall negative total effect. Temperature changes also have a cumulative impact on domestic trade. Labour productivity, population migration and meteorological disasters are the mechanisms through which temperature changes influence Chinese cities' domestic trade. Furthermore, the negative impact of temperature changes is more pronounced in the retail sector and in cities with low air–conditioning penetration. We provide city–level evidence of the relationship between climate change and economic activities from a new perspective of domestic trade, highlight the influential channels and confirm the role of temperature change in impeding the prosperity of domestic trade. [ABSTRACT FROM AUTHOR]

Environmental governance approaches are critical for carbon reduction and energy security. Using the data from government work reports and public search, this paper investigates the impact of government policies and public awareness on carbon emissions. The 'top-down' administrative regulation is found to have more effective in promoting carbon reduction in cities than 'bottom-up' public awareness, and this carbon reduction effect is more pronounced in central, western and lower levels of economic development cities. The findings suggest that regions with higher economic development tend to exhibit greater dependency on carbon, posing challenges in achieving prompt reductions in carbon emissions through governmental policies and public awareness. Additional discoveries indicate that 'top-down' administrative regulation exhibits a certain sustainability, mainly through industrial structure adjustments. This aspect proves beneficial for enhancing the city's developmental path and quality in the long term. [ABSTRACT FROM AUTHOR]

Human capital plays a crucial role in regional innovation and economic progress, which has increasingly been highlighted in research. However, rising housing costs in cities can push talent away, causing brain drain and hindering local innovation. Within this context, China has seen widespread adoption of talent housing policies (THPs) aimed at providing housing assistance for the high-skilled labor force, although the ramifications of these initiatives remain largely underexplored. Based on labor force heterogeneity, this study investigates the effects of THPs targeted at high-skilled labor on the mobility of both high- and low-skilled workers and their consequent impact on regional innovation. Our findings reveal that while THPs bolster the local pool of highly skilled human capital and attract more low-skilled workforce, enhancing regional innovation through labor–skill complementarities, they concurrently elevate housing costs for low-skilled laborers, reducing their long-term settlement intensions and potentially hindering a city's innovation trajectory. [ABSTRACT FROM AUTHOR]

Urban areas can be both detrimental for pollinators or function as suitable habitats, depending on the land-use type, the urban context and the pollinator group in focus. Urban green spaces, including gardens, parks or cemeteries can provide essential resources for a wide range of pollinator groups, like wild bees, hoverflies and beetles. Urban community gardens can be particularly structurally complex and harbour a diverse range of nesting and food resources for pollinators. However, we know little about how garden features may vary with the urban context of gardens and which specific garden features can increase the abundance of pollinators in general and of different pollinator groups. Over two summer seasons, we recorded garden features and pollinators using flower observations in 33 urban community gardens in Munich and Berlin, Germany. We examined how garden features differ amongst urban community gardens from three urbanisation categories, and analysed the effects of garden features such as floral and nesting resources and landscape imperviousness (as indicator of urbanisation) on pollinator abundance, richness and diversity. In more urbanised gardens, flower richness and bare substrate were less prevalent. Flower richness was positively correlated with overall pollinator abundance, richness and diversity as well as with the abundances of all pollinator taxa excluding beetles. Landscape imperviousness was negatively correlated with hoverfly and beetle abundances. Hoverflies also decreased with increasing bare substrate and wasp abundance decreased with increasing deadwood availability. Our findings highlight the important role of flower richness for insect conservation in urban management and show that pollinator taxa react differently to garden features and urbanisation. To support pollinating insects, gardeners can increase flower richness, especially in highly urbanised areas. [Display omitted] [ABSTRACT FROM AUTHOR]

In the context of worldwide biodiversity and wild bee decline, it is increasingly important to better understand the effect of land-use changes on wild bee communities at a global scale. To do so, we studied the effect of city area and urban green spaces layout on wild bee species richness and community composition, as well as on wild bee species with an unfavorable UICN conservation status. This study was based on a large European dataset encompassing 20 cities from France, Belgium and Switzerland. We found a mean wild bee species richness in cities of 96 ± 48 (SD), showing that this species richness was highly variable among cities. The main factor positively influencing wild bee species richness in cities was the area of the city. Conversely, species richness was not significantly related to the total area of urban green spaces in a given city, measured as the spatial extent of urban parks, wastelands and other semi-natural habitats, excluding urban private gardens. Species with conservation status were quite scarce in urban environments, especially when compared to the European Red List of Bees, and we could not link their presence to either city or urban green space area. Dissimilarities in wild bee species community compositions were not associated with any of the studied characteristics of cities. We found that the dissimilarity of wild bee community composition among cities was mainly driven by the rarest species, as the most common ones were found in a majority of the cities sampled. Overall, these results emphasize that larger cities host more wild bee species, but are no refuge for the ones with concerning conservation status. Thus, stakeholders are encouraged to design their cities in favor of biodiversity to better support wild bee communities, and perhaps mitigate the established effect of the urban ecological filter. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate an acoustic environment based on spatial configurations. To achieve this objective, two types of data were utilized. First, the urban acoustic data was collected from 96 measurements based on equivalent continuous A-weighted sound pressure levels across three different urban areas in Cairo, Egypt, during weekends and at night. The data was plotted on a contour map in an effort to investigate their distribution in the urban area. Secondly, the data was collected using DepthMapX software, and in this way, spatial analysis was produced with diverse spatial attributes. Moreover, on-site observations of pedestrian and traffic rates were made, and land use distribution was observed. Statistical analysis was also conducted using the Statistical Package for Social Sciences (SPSS). Our statistical analysis showed that the value of sound pressure level (L Aeq) is greatly influenced by spatial attributes in highly accessible spatial configurations, with Normalized Angular Integration (NAIN) being the most accurate predictor of sound pressure level. Our findings also verified the existence of a high correlation between commercial and mixed land uses and (L Aeq). Additionally, this study revealed that the urban sound model can predict sound pressure level (L Aeq) in an urban setting. This dataset functions as a valuable resource for future research, urban designers, and policymakers who are addressing sustainable issues pertaining to soundscape, noise pollution, and urban planning. [ABSTRACT FROM AUTHOR]

Combining microbiome science and biointegrated design offers opportunities to help address the intertwined challenges of urban ecosystem degradation and human disease. Biointegrated materials have the potential to combat superbugs and remediate pollution while inoculating landscape materials with microbiota can promote human immunoregulation and biodiverse green infrastructure, contributing to 'probiotic cities'. [ABSTRACT FROM AUTHOR]

This paper develops a spatial equilibrium model for a competitive two-city system consisting of a high-income and a low-income city. Using this model, we investigate the effects of intracity and intercity commuting subsidies on such urban performances as spatial structures, residents' utility, and social welfare of cities and the system. The three unilateral subsidy scenarios and two subsidy competition scenarios are investigated individually. Results show that intercity commuting subsidy gives residents incentives to reside in the low-income city and intercity commuting to the high-income city, while intracity commuting subsidies lead to the inflow of population. Subsidy competitions increase residents' utility and mitigate the impacts of unilateral subsidies on the social welfare of the system. A numerical example and case study based on city pairs of Jing-Jin-Ji Urban Agglomeration in China are conducted to examine the proposed model. • Establish a spatial equilibrium model in a competitive two-city system. • Investigate the effects of unilateral intracity and intercity commuting subsidies on urban performances. • Explore the subsidy competitions between cities and compare results with unilateral subsidies scenarios. • Provide a case study based on Jing-Jin-Ji Urban Agglomeration in China. [ABSTRACT FROM AUTHOR]

Much of prior research has shown a growing interest in determinants of subjective well-being (SWB). However, relatively less research has explored the causal effects of commute and built environment (BE) on SWB, and there is little knowledge regarding how these connections differ between household members. The study examines both cross-sectional and longitudinal connections between commute, BE, and SWB, as well as the variations in these connections between couples, by analyzing longitudinal survey data of dual-earner households from Chinese cities. The results indicate that the increase in commute duration results in lower SWB. Shifting to active modes is shown to increase SWB. Nonetheless, shifting in the opposite direction shows no significant effect. All BE changes are correlated with the husbands' SWB changes, whereas only changes in neighborhood categories and neighborhood density appear to matter for wives. The findings indicate that planning strategies can complement transport policies aimed at enhancing SWB. • The study examines both cross-sectional and longitudinal connections between commute, BE, and SWB. • The increase in commute duration leads to declined SWB. • Shifting to active modes is shown to increase SWB. • Husbands' SWB is more sensitive to changes in BE. • There are variations in the determinants of SWB between couples. [ABSTRACT FROM AUTHOR]

International agreements and European policies emphasise the necessity to reduce transport externalities, particularly by focusing on greenhouse gas (GHG) emissions. This reduction should align with improved accessibility to major urban areas, which is a goal explicitly associated with the Trans-European Transport Network (TEN-T). However, the correlation between these two objectives is not necessarily straightforward, as an increase in travel demand may contribute to the growth in transport externalities. This study economically evaluates the transport externalities generated along the Italian segment of the Brenner axis, which is the central part of the TEN-T Scandinavian–Mediterranean corridor. The aim of the analysis is twofold: (i) to ascertain whether the evolution of travel demand over the last decade aligns with European objectives on transport externalities; (ii) to project the expected effects to 2030 and 2040 under alternative scenarios. Existing data fail to reveal a clear trend, owing to fluctuating travel demands in recent years. Instead of indicating a generalised reduction in externalities, the data reflect a redistribution of costs among categories, with less effects from local pollutants and higher congestion and accident costs. The anticipated increase in travel demand is likely to exacerbate these externalities, thus further increasing road congestion and accident costs. This increase is not expected to be fully offset by the reduction in air and GHG emissions despite the enhanced efficiency of the vehicular fleet. The modal shift from road to rail, as well as the ongoing digitalisation processes, are imperative for effective road traffic management and reducing costs along the corridor. • Long-distance road transport as a main source of transport externalities. • Quantification and evaluation for the Italian mountain stretch of the Brenner corridor. • Development of alternative transport and infrastructural scenarios. • Technological development alone not sufficient for the reduction of external costs. • Modal shift towards rail as essential policy to meet EU energy targets. [ABSTRACT FROM AUTHOR]

Sustainable development has been the guiding political principle worldwide since the adoption of the UN SDGs in 2015. Transport is of highest relevance for meeting this ambition; it enables people to move to destinations to meet their needs, and it causes substantial negative effects in the social, economic, and environmental dimensions. Cities are of highest relevance for transport because of their prevalence, and because challenges and opportunities are particularly pronounced in cities, but few attempts have been made to evaluate how cities translate the higher-level sustainability ambitions to their local contexts. Based on a survey of 402 municipalities in Germany, this study investigates local stakeholders' priorities in terms of sustainable urban mobility (SUM). Expert planners in local administrations assign higher priority to all SUM aspects than this is the case in the official local strategic planning objectives, such as those formulated in Sustainable Urban Mobility Plans (SUMPs), with congestion being the only exception. Accessibility and further domain-specific aspects consistently get higher priority than the environmental effects of transport. Local stakeholders consistently commit first and foremost to the function of transport systems and give the minimization of negative effects only secondary priority. Priorities assigned to the SUM aspects are higher in larger cities than in smaller cities, particularly for the expert planners' assessments. Further studies with similar designs in other parts of the world would help to better understand the transferability of the mechanisms identified in this study and support higher-level efforts to achieve sustainability goals. • Expert survey on local priorities for sustainable mobility in 402 German cities. • Larger cities give higher priority to sustainable mobility than smaller cities. • Accessibility generally prioritized over environmental aspects. • Importance Performance Analysis proves suitable for analyzing planners' priorities. [ABSTRACT FROM AUTHOR]

Faced with pollinator declines, cities could serve as refuges for biodiversity conservation by managing floral resources in public green spaces. Ornamental plants could play an important role in attracting pollinators because they form part of urban floral management. However, knowledge of how their floral traits respond to drought is lacking, and it is unknown whether they will be suitable for pollinators under future climates. The main objective of this study was to determine the covariation of floral traits of ornamental plant species and effects of drought on them. To this end, in a city greenhouse we measured floral traits of eight ornamental species commonly used in urban green spaces in France. We subjected the plants to a control treatment or a drought treatment, reducing the volume and frequency of watering. We observed interspecific variability in floral traits among these species and a change in covariation between the traits pollen quantity and nectar quantity in the drought treatment. Drought influenced morphological traits related to floral display more than other floral traits, with mean decreases of 28 % in floral height, 35 % in floral area and 58 % in the number of floral units. Ornamental plants seemed attractive to different morphotypes of pollinators depending on their floral unit number, nectar sugar concentration or nectar tube depth, with most visits made by Hymenoptera. These results are expected to encourage green-space managers to select urban plants according to their functional characteristics and adapt their choice of plants to climate change. [ABSTRACT FROM AUTHOR]

Rail transit system plays an important role in connecting the urban center, new towns and suburbs in the metropolitan area. Exploring the methods of integrating rail transit and land use in different locations is essential to improve trip rates and promote transit-oriented development (TOD). Taking Wuhan, China, as a case study, this research uses a cellular automaton-based random forest (CA-RF) model to simulate land use change surrounding rail transit by capturing the impact differences in mother city (MC) and new towns (NT). An impact area identification model is proposed to recognize the most sensitive threshold of land use change in both MC and NT stations, which are 1000m and 1200m, respectively. The characteristics of land use change from 2010 to 2020 are analyzed and compared. The CA-RF model calibration shows that transportation and spatial accessibility present wide variations in driving land use change surrounding the MC and NT stations. The high accuracy of CA-RF model, which is 88.1% for MC and 82.1% for NT, indicating its effectiveness in quantifying the non-linear relationship of land use change and spatial attributes. The forecasted land use maps for proposed rail stations provide a reference for governments and planners in policy intervention and decision-making. This research framework can be applied to other metropolitans to explore the regulations of land use development and promote transit-oriented sustainable development. • Explore the driving mechanisms for land use change within rail transit stations area in different metropolitan areas. • Examine the non-linear relationship between land use change and spatial attributes by proposing a CA-RF model. • Develope a simulation framework to visualize future land use maps considering the impacts of rail transit. [ABSTRACT FROM AUTHOR]

In the era of E-commerce and globalization, the logistics industry has become a new driving force for local economic development, with government-led logistics parks planned and constructed as a powerful policy instrument. Skeptical about whether logistics parks really take effect as expected, this paper investigates the local process of creative destruction in the logistics industry, focusing on how government-led logistics parks bridge between firm exit and firm entry during industrial renewal. Using firm-level data of third-party logistics firms in China from 2003 to 2021 and adopting system GMM estimator method, we verify that previous exit contributes to future entry but varies by the firm type and the city's importance in the regional transport network. Furthermore, we find two major roles of government-led logistics parks: (1) accelerating this process by providing the platform where various resources can be reused and reorganized into high-quality new logistics firms; and (2) prioritizing the rebirths from local existing firms over arrivals from other cities, though with some level of local protectionism. Government policies and planning decisions should maintain such function without inhibiting regional market integration. • The spatial and temporal dynamics of logistics firms are affected by government policies. • The previous exit of logistics firms in a city would affect the future entry of new logistics firms in the same city. • Heavy reliance on existing resources often leads to great multiplier effect. • Logistics parks encourage the firm entry indirectly by facilitating the resource transition from exiting firms. • What logistics parks provide is a place where complexity in the logistics system can be managed and developed. [ABSTRACT FROM AUTHOR]

The empirical evidence in the existing literature primarily supports the positive association of transit-oriented development (TOD) with transit use. However, indirect relationships between TOD and transit use may be observed due to TOD-induced gentrification and spatial autocorrelation. This research examined the relationships between TOD, gentrification, and transit use with the consideration of spatial autocorrelation. The study observations were from the gentrifiable neighborhoods in Taipei City, Taiwan, and were analyzed using simultaneous equation models and spatial regression methods. Empirical results reveal three major findings: 1) A positive and direct association of TOD-ness with the modal share of transit substantially occurs and confirms the findings in the existing literature. 2) A negative and indirect association of TOD with transit use mediated by gentrification may occur under the moderation of rising car ownership. 3) A positive spatial autocorrelation of transit use substantially occurs between adjacent neighborhoods. These findings prompt local administrations to implement TOD policies containing or being accompanied by instruments inhibiting car ownership throughout urban areas rather than just along major transit corridors. • A positive and direct association of TOD-ness with the modal share of transit substantially occurs. • A negative and indirect association of TOD with transit use mediated by gentrification may occur under the moderation of rising car ownership. • A positive spatial autocorrelation of transit use substantially occurs between adjacent neighborhoods. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of high-speed rail (HSR) network improvement on the consumption synergy of the Beijing-Tianjin-Hebei region by using the panel data of 13 prefectural-level cities from 2006 to 2021. The results show that: (1) The improvement of the HSR network in the Beijing-Tianjin-Hebei region has a significant positive impact on raising overall regional consumption levels. (2) The HSR network improvement has a heterogeneous impact on consumption in different cities within the Beijing-Tianjin-Hebei region. (3) The promotional effect on peripheral cities is greater than on central cities, thereby promoting the coordinated consumption development of the Beijing-Tianjin-Hebei region. The findings of this study have important policy implications, confirming that the construction of the HSR network can narrow the consumption gap within the region and promote consumption synergy across the region. • This paper investigated the impact of HSR network improvement on consumption synergy in Beijing-Tianjin-Hebei region. • This paper found that the construction of the HSR network can promote consumption synergy across the region. • This paper applied groups of instruments and social network analysis to guarantee the robustness of the results. • The findings have important policy implications to the government and railway department. [ABSTRACT FROM AUTHOR]

Fine classification of city-scale buildings using satellite imagery is a crucial research area with significant implications for urban planning, infrastructure development, and population distribution analysis. However, the task faces great challenges due to low-resolution overhead images acquired from high-altitude space-borne platforms and the long-tailed sample distribution of fine-grained urban building categories, leading to a severe class imbalance problem. To address these issues, we propose a deep network approach to the fine-grained classification of urban buildings using open-access satellite images. A Denoising Diffusion Probabilistic Model (DDPM) based super-resolution method is first introduced to enhance the spatial resolution of satellite images, which benefits from domain-adaptive knowledge distillation. Then, a new fine-grained classification network with Category Information Balancing Module (CIBM) and Contrastive Supervision (CS) technique is proposed to mitigate the problem of class imbalance and improve the classification robustness and accuracy. Experiments on Hong Kong data set with 11 distinct building types revealed promising classification results with a mean Top-1 accuracy of 60.45%, which is on par with street-view image based approaches. A comprehensive ablation study demonstrates that the CIBM and CS modules improve Top-1 accuracy by 2.6% and 3.5%, respectively, over the baseline approach. In addition, these modules can be easily integrated into other classification networks, achieving similar performance improvements. This research advances urban analysis by providing an effective solution for detailed classification of buildings in complex mega-city environments using only open-access satellite imagery. The proposed technique can serve as a valuable tool for urban planners, aiding in the understanding of economic, industrial, and population distribution within cities and regions, ultimately facilitating informed decision-making in urban development and infrastructure planning. Data and code will be publicly available at https://github.com/ZhiyiHe1997/UB-FineNet. [ABSTRACT FROM AUTHOR]

Informal settlements' geographic and demographic mapping is essential for evaluating human-centric sustainable development in cities, thus fostering the road to Sustainable Development Goal 11. However, fine-grained informal settlements' geographic and demographic information is not well available. To fill the gap, this study proposes an effective framework for both fine-grained geographic and demographic characterisation of informal settlements by integrating openly available remote sensing imagery, points-of-interest (POI), and demographic data. Pixel-level informal settlement is firstly mapped by a hierarchical recognition method with satellite imagery and POI. The patch-scale and city-scale geographic patterns of informal settlements are further analysed with landscape metrics. Spatial-demographic profiles are depicted by linking with the open WorldPop dataset to reveal the demographic pattern. Taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China as the study area, the experiment demonstrates the effectiveness of informal settlement mapping, with an overall accuracy of 91.82%. The aggregated data and code are released (https://github.com/DongshengChen9/IF4SDG11). The demographic patterns of the informal settlements reveal that Guangzhou and Shenzhen, the two core cities in the GBA, concentrate more on young people living in the informal settlements. While the rapid-developing city Shenzhen shows a more significant trend of gender imbalance in the informal settlements. These findings provide valuable insights into monitoring informal settlements in the urban agglomeration and human-centric urban sustainable development, as well as SDG 11.1.1. [ABSTRACT FROM AUTHOR]

Linking meteorology and air pollutants is a key challenge. The study investigated meteorological effects on PM 2.5 concentration using the advanced convergent cross mapping method, utilizing hourly PM 2.5 concentration and six meteorological factors across eight provinces and cities in Vietnam. Results demonstrated that temperature (ρ = 0.30) and radiation (ρ = 0.30) produced the highest effects, followed by humidity (ρ = 0.28) and wind speed (ρ = 0.24), while pressure (ρ = 0.22) and wind direction (ρ = 0.17) produced the weakest effects on PM 2.5 concentration. Comparing the ρ values showed that temperature, wind speed, and wind direction had greater impacts on PM 2.5 concentration during the dry season whereas radiation had a more influence during the wet season; Southern stations experienced larger meteorological effects. Temperature, humidity, pressure, and wind direction had both positive and negative influences on PM 2.5 concentration, while radiation and wind speed mostly had negative influences. During PM 2.5 pollution episodes, there was more contribution of meteorological effects on PM 2.5 concentration indicated by ρ values. At contaminated levels, humidity (ρ = 0.45) was the most dominant factor affecting PM 2.5 concentration, followed by temperature (ρ = 0.41) and radiation (ρ = 0.40). Pollution episodes were pointed out to be more prevalent under higher humidity, higher pressure, lower temperature, lower radiation, and lower wind speed. The ρ calculation also revealed that lower temperature, lower radiation, and higher humidity greatly accelerated each other under pollution episodes, further enhancing PM 2.5 concentration. The findings contributed to the literature on meteorology and air pollution interaction. [ABSTRACT FROM AUTHOR]

• High tropospheric NO 2 VCDs were detected in Rosario, area of more than 1 million people. • Rural areas showed high NO 2 levels during the fire events. • We analyzed tropospheric NO 2 VCD and air masses by using TROPOMI data and HYSPLIT. • Maximum daily FRP value of 10 GW was detected by VIIRS/S-NPP. Wildfires in the Paraná River Delta started to be a common situation in the year 2008 and during the first years of the 2020́s decade: 2020, 2021, 2022. These fires affected natural areas, primarily the islands within the delta, situated in front of Rosario city (32.95 °S, 60.67 °W, 25 meters above sea level (m.a.s.l.)), Argentina. They mostly occur during the period between June and September each year and are more intense when a strong La Niña event is present. The aim of this study is to examine the association between the propagation of high intensity nitrogen dioxide ( NO 2 ) plumes and the significant fire events that occurred in the Paraná River Delta from 6 to 17 September 2022. Satellite data of NO 2 obtained from the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency (ESA) Sentinel-5 Precursor satellite, air mass forward trajectories performed with The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), Fire Radiative Power (FRP) data provided by Visible Infrared Imaging Radiometer Suite (VIIRS) on board The National Oceanic and Atmospheric Administration - 20 (NOAA-20) and Suomi National Polar-orbiting Partnership (S-NPP) satellites, Aerosol Optical Depth (AOD) from VIIRS S-NPP and Smoke Injection Height from Multi-Angle Implementation of Atmospheric Correction (MAIAC) Thermal Technique were employed. The trajectories followed by the air masses coming from the major fire sources locations nearby Rosario city and its surrounding area, were analyzed at altitudes of 20, 500, 1000, 1500 and 2000 m above ground level (AGL) in order to evaluate the impact of the NO 2 clouds present in the atmosphere and carried by the winds, at different sites of Rosario and its adjacent region. The NO 2 plumes has the potential to pose a significant health risk for this region, inhabited by an approximate population of one and a half million individuals. This risk is contingent upon the altitude where the highest levels of NO 2 in the tropospheric column are found. Tropospheric vertical column densities (VCDs) of NO 2 in the range of 4.68 × 10 14 to 1.66 × 10 16 molecules/cm2 were determined. The results indicate a robust correlation between elevated tropospheric NO 2 VCD values and intense fires, as characterized by their FRP. Additionally, high tropospheric NO 2 VCDs were observed to impact cities and towns located in close proximity to the fires. In particular, the unusually high tropospheric NO 2 VCDs determined for the towns of Fighiera and Pueblo Esther, situated along the coast and near the Paraná River Delta, are noteworthy. This is uncommon considering they are small towns in rural areas that typically have good air quality. The results regarding FRP, provided by VIIRS on board NOAA-20 and S-NPP satellites, indicate that the fire characterization of hotspots during the considered period had a mean value in the range of 20.17–21.47 MW. On specific days (12, 13 and 16 September 2022), the cumulative (total) daily values were very high, ranging from 2000 to 10000 MW. Furthermore, on 12 and 13 September 2022, the smoke aerosols did not reach significant altitudes in the atmosphere, remaining within the range of 0 to 1500 m AGL. During the fire period, AOD values close to 1 were observed within the fire plume. Notably, Puerto San Martín (0.27), San Lorenzo (0.22), and Ibarlucea (0.20) recorded higher average AOD values compared to other sites. The remaining sites generally exhibited lower average AOD values, with a slight distinction between rural locations (Pueblo Esther: 0.14 and Fighiera: 0.14) and the city center of Rosario (0.09). [ABSTRACT FROM AUTHOR]

A good understanding of the behavior of the atmosphere is a key factor in radio wave propagation and link's design. This study investigated the influence of refractivity gradient, effective earth radius factor (k-factor) and geo-climatic factor (K-factor) on radio communication over the cities of Kaduna, Katsina and Sokoto, in Northwestern parts of Nigeria. Forty-one year's secondary data (1980–2020) of temperature, pressure and humidity at the surface 12, 100 and 250 m above ground level retrieved from European Centre for Medium-Range Weather Forecasts (ECMRWF) ERA-5 reanalysis were used for the study. The three secondary radio-climatic parameters under investigation were computed and analyzed using latest ITU-R (Rec.P.453-14 (08/2019)) Models. It was observed that secondary radio-climatic variables exhibit seasonal type dependence. The research also reveals that the secondary radio-climatic variables depend on location, with all the study locations having different values. The highest value of refractivity gradient obtained is about −75.06 (N-units / km) in the month of February in Sokoto while the least of about −162.65 (N-units/km) was recorded in Kaduna in September. The value of the refractivity gradient is higher during the dry season compared to the wet season months with Sokoto recording the highest values for more than half of the months, followed by Katsina. Kaduna recorded highest number of lowest values of refractivity gradient. For the geoclimatic factor, it was revealed that Kaduna has an average maximum geoclimatic factor of 14.0000E-5 in September and an average minimum of 9.6677E-05 in February. Furthermore, the obtained values of k factor values for the study areas are higher than the standard value of, 4 3 (1.33). The k-factor in Kaduna ranges from 1.69 to 2.16 with mean value of 1.85 for dry season while for the wet season it ranges from 2.66 to 4.12 with a mean value of 3.74; the overall mean value for Kaduna is 2.80. In Katsina, it ranges from 1.66 to 2.20 with mean value of 1.81 for dry season while for the wet season it ranges from 1.95 to 4.00 with a mean value of 3.27; the overall mean value is 2.54. In Sokoto it ranges from 1.60 to 2.30 with mean value of 1.78 for dry season while for the wet season it ranges from 1.72 to 3.45 with a mean value of 2.59; the overall mean value is 2.19. The interpretation of this is that, radio signal propagation in the Northwest region of Nigeria is super-refractive. The overall findings of this research are essential for estimating location-dependent fade margins, which are useful for the design of wireless communication links for the region. [ABSTRACT FROM AUTHOR]

China has steadfastly pledged its dedication to accomplishing carbon peaking by 2030 and achieving carbon neutrality before 2060, a commitment widely recognized as the Dual Carbon Goal (DCG). The proposition of China's DCG presents formidable challenges for the advancement of the transport sector due to its significant contribution to carbon emissions. Consequently, new carbon abatement constraints have been enforced on carbon emissions within the Chinese transport sector. In pursuit of the carbon peaking goal, this research introduces the environmental context-dependent data envelopment analysis approach. The approach is employed to identify sustainable performance targets for the Chinese transport sector at the city level, while considering carbon abatement constraints. These sustainable performance targets not only provide insights on enhancing the environmental performance of these cities with minimum effort, but also offer a comprehensive pathway towards carbon peaking cities in the Chinese transport sector. • A pathway towards carbon peaking cities in the Chinese transport sector is examined. • An environmental context-dependent data envelopment analysis approach is proposed. • Policy implications for the Chinese transport sector are presented. [ABSTRACT FROM AUTHOR]

Travelers often change their behavior in reaction to adverse weather conditions. This paper seeks to conduct an empirical evaluation of both ordered and unordered discrete outcome frameworks for examining the adaptive behavior decisions of intercity travelers and investigate the varying effects of explanatory factors on different alternatives of adaptive behavior during adverse weather. The data from 754 respondents in the Beijing-Tianjin-Hebei urban agglomeration, China are collected by a two-phase survey instrument. To capture the unobserved heterogeneity more effectively, this paper develops three advanced models to investigate the variations in intercity travel behavior during adverse weather. Four alternative adaptive behaviors are determined as outcome variables: maintaining original travel plans, changing only the intercity mode, changing the departure date, and canceling the trip, while potential influencing factors including adverse weather conditions, trip-related characteristics, individual attributes and urban agglomeration attributes are statistically assessed. The results indicate that the unordered models consistently outperform their ordered counterparts, and the incorporation of multilayer heterogeneity enhances the model fit. Furthermore, significant factors and their coefficient values vary across the different adaptive behavior alternatives. Intercity travelers demonstrate a higher probability of changing departure dates or canceling trips during snowy and windy days compared to rainy and foggy days. Trains exhibit higher flexibility and reliability during adverse weather, and access attributes significantly affect intercity travel adaptive behavior. Additionally, the analysis of individual and urban agglomeration attributes uncovers variations in adaptive behavior among individuals and cities. These findings provide profound insights into the complexities and variations of intercity travel behavior during adverse weather, and propose practical strategies to mitigate the detrimental impacts of adverse weather on intercity travelers. • Adaptive behavior of intercity travelers during adverse weather is investigated. • Unordered framework outperforms ordered counterparts in adaptive behavior study. • Multilayer unobserved heterogeneity in the adaptive behavior is accounted for. • The varying effects of explanatory factors on different adaptive alternatives are examined. • Practical strategies are proposed to mitigate negative impacts of adverse weather. [ABSTRACT FROM AUTHOR]

Climate change is a major environmental issue, while reducing carbon dioxide emissions is viewed as a vital measure against global warming. The CHINA RAILWAY Express (CRE) could attract or foster new export-oriented industries by generating new profitable export opportunities and enhancing access to European markets. This study focused on the unintended effect of the CRE policy on carbon dioxide emissions reduction, which stems from its promotion of industry development. We used the synthetic difference-in-differences approach to derive reliable estimation of the CRE's unintended low-carbon effect. After controlling for the influence of other emission sectors and other low-carbon policies, the estimated results indicate that the CRE only reduced carbon dioxide emissions in the 12 cities with regular CRE services. The unintended policy effect decreased carbon dioxide emissions, on average, by 9.18%. Further heterogeneous analysis shows that the CRE's effect is positively correlated with the numbers of CRE trains. Moreover, the CRE has a heterogeneous impact on high-carbon and low-carbon sectors. Because the CRE can promote the exports of low-carbon sectors to Europe rather than those of high-carbon sectors, the CRE has a prominent impact on reducing average carbon dioxide emissions and improving the industrial structure. Formal mechanism analysis confirms that the impact of the CRE on carbon dioxide emissions actually occurs through the mechanism of industrial structure upgrading. Our results reveal the CRE's unintended environmental gains and offer insight for governments that hope to simultaneously reduce carbon dioxide emissions and promote economic growth. • CRE policy can have unintended environmental gains, such as reduced carbon emission. • CRE can bring in profitable export opportunities and enhance European market reach. • CRE's driving power for industrial upgrades shows unintended environmental gains. • CRE's reduction of CO 2 emissions is significant in regularly operational CRE cities. • CRE's unintended low-carbon policy impacts positively correlate with CRE train numbers. [ABSTRACT FROM AUTHOR]

We propose a social network-aware approach to study socio-economic segregation. The key question that we address is whether patterns of segregation are more pronounced in social networks than in the common spatial neighborhood-focused manifestations of segregation. We, therefore, conduct a population-scale social network analysis to study socio-economic segregation at a comprehensive and highly granular social network level. For this, we utilize social network data from Statistics Netherlands on 17.2 million registered residents of the Netherlands that are connected through around 1.3 billion ties distributed over five distinct tie types. We take income assortativity as a measure of socio-economic segregation, compare a social network and spatial neighborhood approach, and find that the social network structure exhibits two times as much segregation. As such, this work complements the spatial perspective on segregation in both literature and policymaking. While at a widely used unit of spatial aggregation (e.g., the geographical neighborhood), patterns of socio-economic segregation may appear relatively minimal, they may in fact persist in the underlying social network structure. Furthermore, we discover higher social network segregation in larger cities, shedding a different light on the common view of cities as hubs for diverse socio-economic mixing. A population-scale social network perspective hence offers a way to uncover hitherto "hidden" segregation that extends beyond spatial neighborhoods and infiltrates multiple aspects of human life. • Policy focus on administrative boundaries obscures segregation in social networks. • Social networks exhibit two times as much segregation as administrative neighborhoods. • Cities, commonly seen as hubs of diverse mixing, are sites of high segregation. • Network segregation should be included into social cohesion evaluation frameworks. [ABSTRACT FROM AUTHOR]

• Cities benefit from nutrient circularity integrating waste and local agriculture. • Significant benefits from biogas generation and avoiding mixed waste treatment. • Nutrient concentrations in urban agricultural soils limit application of compost. • Local regulations and soil quality hinder nutrient circularity in urban areas. Cities face the challenges of supplying food and managing organic municipal solid waste (OMSW) sustainably amid increasing urbanization rates. Urban agriculture (UA) can help with this effort by producing local crops that are fertilized with nutrients recovered from compost generated from OMSW. This research aims to determine the potential of OMSW compost to supply the nitrogen-phosphorus-potassium (NPK) demand of UA and the environmental benefits of replacing mineral fertilizer from a life cycle perspective. The Metropolitan Area of Barcelona (AMB) serves as the case study given its commitment to reuse biowaste according to the Revised Waste Framework Directive and to promote UA as a signing member of the Milan Urban Food Policy Pact. Based on crop requirements and farmer surveys, we find that the annual NPK demands of the agricultural fields of the AMB that cover 5,500 ha and produce 70,000 tons of crops are approximately 769, 113, and 592 tons of NPK, respectively. Spatial material flow analysis and life cycle assessment were applied to found that the current waste management system can potentially substitute 8 % of the total NPK demanded by UA with compost, reduce the impacts by up to 39 % and yield savings in global warming of 130 %. The more ambitious future scenario of 2025 can potentially substitute 21 % of the total NPK demand and reduce environmental impacts up to 1,049 %, depending on the category considered. Avoiding processing of mixed OMSW, mineral fertilizer replacement and cogeneration of electricity from biogas are the major contributors to these environmental savings. [ABSTRACT FROM AUTHOR]

• A model is developed to assess the effectiveness of CDWM on a city scale. • Performance levels and weaknesses in CDWM practices of the GBA are identified. • Differences of CDWM across GBA cities are revealed through empirical study. The growing generation of construction and demolition waste (CDW) has emerged as a prominent challenge on global environmental agendas. However, the effectiveness of CDW management (CDWM) strategies varies among cities. Existing literature predominantly evaluates the effectiveness of CDWM at the project level, offering a localized perspective that fails to capture a city's comprehensive CDWM profile. This localized focus has certain limitations. To fill this gap in city-scale evaluations, this study introduces a novel model for assessing CDWM effectiveness at the municipal level. An empirical investigation was conducted across 11 cities within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) to operationalize this model. The model defines five distinct levels of CDWM effectiveness. Findings indicate that Hong Kong consistently achieves the highest level (level I), while the majority of cities fall within levels III and IV. This pattern suggests that CDWM effectiveness in the GBA is moderately developed, with uneven progress in CDW management outcomes and supporting systems. Essentially, there is a lack of synchronous development of CDWM results and guarantee systems. The proposed evaluation model enriches existing CDWM research field and offers a framework that may inform future studies in other countries. [ABSTRACT FROM AUTHOR]

• Field experiment in mandatory recycling scheme tests effectiveness of door stepping. • Majority of households in mandatory recycling schemes separates waste correctly. • Minority of households is responsible for most miss sorting. • Door stepping does not influence behavior of households in mandatory schemes. • Door stepping can improve recycling behavior in voluntary recycling schemes. Household organic waste has great potential for closing nutrient cycles in agriculture. This requires proper waste separation by households. Personal communication at the doorstep potentially improves household waste separation behaviour but it is expensive and findings from existing research are mixed. Based on results of previous studies and from a quasi-experiment with non-equivalent groups design in two German municipalities, this paper argues that efficiency of personal communication depends on its context. It can positively influence behaviour when recycling is voluntary and participation rates are low. However, it has no significant effects if recycling is mandatory. One explanation could be different perceptions of recycling in mandatory and voluntary schemes. In voluntary schemes door stepping can activate the intrinsic motivation of households. In mandatory schemes, all households need to participate irrespective of intrinsic motivation. This research shows that this creates a situation in which a small share of households is responsible for almost all contamination. This can be overcome by considering extrinsic factors that affect recycling behaviour. The paper recommends further research to understand which combination of incentives, sanctions and information is efficient in affecting behaviour change in mandatory recycling schemes. [ABSTRACT FROM AUTHOR]

This examine introduces a novel personalised recommendation technique for cultural and innovative merchandise in traveler cities, leveraging the superior abilities of BERT4Rec along designated user photos to noticeably enhance the advice machine's precision and customization. with the aid of undertaking an in-intensity evaluation of users' historical conduct, the studies harnesses the state-of-the-art deep mastering and self-attention mechanisms intrinsic to BERT4Rec. This technique adeptly captures the nuanced long-range dependencies in user activities, imparting a profound perception into the styles and selections that define user behavior. The innovation extends to integrating these dynamic behavioral insights with the static demographic statistics of users—such as age, gender, and occupation—to forge a extra nuanced and whole user profile. This holistic view not solely mirrors the users' beyond interactions however also weaves in fundamental demographic information, paving the way for tailored and nuanced suggestions. The deployment of BERT4Rec stands as a testomony to its prowess in decoding complex consumer engagement tendencies and tendencies, whilst the fusion with consumer pix extensively bolsters the system's potential to cater to the various and specific desires of users.Empirical proof underscores the prevalence of this technique over modern tourism product advice algorithms, marking a giant stride in the realm of cultural innovative product recommendations inside traveler cities. furthermore, this paper's insights and methodologies provide treasured implications for reinforcing advice structures across severa domain names. [ABSTRACT FROM AUTHOR]