Remote monitoring applications in urban vehicular ad-hoc networks (VANETs) enable authorities to monitor data related to various activities of a moving vehicle from a static infrastructure. However, urban environment constraints along with various characteristics of remote monitoring applications give rise to significant hurdles while developing routing solutions in urban VANETs. Since the urban environment comprises several road intersections, using their geographic information can greatly assist in achieving efficient and reliable routing. With an aim to leverage this information, this article presents a receiver-based data forwarding protocol, termed Intersection-based Link-adaptive Beaconless Forwarding for City scenarios (ILBFC). ILBFC uses the position information of road intersections to effectively limit the duration for which a relay vehicle can stay as a default forwarder. In addition, a winner relay management scheme is employed to consider the drastic speed decay in vehicles. Furthermore, ILBFC is simulated in realistic urban traffic conditions, and its performance is compared with other existing state-of-the-art routing protocols in terms of packet delivery ratio, average end-to-end delay and packet redundancy coefficient. In particular, the results highlight the superior performance of ILBFC, thereby offering an efficient and reliable routing solution for remote monitoring applications.
The construction of low-carbon cities is an essential component of sustainable urban development. However, there is a lack of a comprehensive low-carbon city design and evaluation system that incorporates "carbon sink accounting-remote sensing monitoring-numerical modelling-design and application" in an all-around linkage, multi-scale coupling, and localized effects. This paper utilizes the Citespace tool to evaluate low-carbon city design applications by analyzing literature in the Web of Science (WOS) core collection database. The results reveal that low-carbon cities undergo four stages: "measurement-implementation-regulation - management." The research themes are divided into three core clustering evolutionary pathways: "extension of carbon sink functions," "spatialisation of carbon sink systems," and "full-cycle, full-dimensional decarbonisation." Applications include "Utility studies of multi-scale carbon sink assessments," "Correlation analysis of carbon sink influencing factors," "Predictive characterisation of multiple planning scenarios," and "Spatial planning applications of urban sink enhancement." Future low-carbon city construction should incorporate intelligent algorithm technology in real-time to provide a strong design basis for multi-scale urban spatial design with the features of "high-precision accounting, full-cycle assessment and low-energy concept."
Delay Tolerant Network (DTN) multi-copy routing protocols are privileged to create and transmit multiple copies of each message that causes congestion and some messages are dropped. This process is known as reactive drop because messages were dropped re-actively to overcome buffer overflows. The existing reactive buffer management policies apply a single metric to drop source, relay and destine messages. Hereby, selection to drop a message is dubious because each message as source, relay or destine may have consumed dissimilar magnitude of network resources. Similarly, DTN has included time to live (ttl) parameter which defines lifetime of message. Hence, when ttl expires then message is automatically destroyed from relay nodes. However, time-to-live (ttl) is not applicable on messages reached at their destinations. Moreover, nodes keep replicating messages till ttl expires even-though large number of messages has already been dispersed. In this paper, we have proposed Priority Queue Based Reactive Buffer Management Policy (PQB-R) for DTN under City Based Environments. The PQB-R classifies buffered messages into source, relay and destine queues. Moreover, separate drop metric has been applied on individual queue. The experiment results prove that proposed PQB-R has reduced number of messages transmissions, message drop and increases delivery ratio.
The exposure-lag response of air temperature on daily COVID-19 incidence is unclear and there have been concerns regarding the robustness of previous studies. Here we present an analysis of high spatial and temporal resolution using the distributed lag non-linear modelling (DLNM) framework. Utilising nearly two years' worth of data, we fit statistical models to twelve Italian cities to quantify the delayed effect of air temperature on daily COVID-19 incidence, accounting for several categories of potential confounders (meteorological, air quality and non-pharmaceutical interventions). Coefficients and covariance matrices for the temperature term were then synthesised using random effects meta-analysis to yield pooled estimates of the exposure-lag response with effects presented as the relative risk (RR) and cumulative RR (RRcum). The cumulative exposure response curve was non-linear, with peak risk at 15.1 °C and declining risk at progressively lower and higher temperatures. The lowest RRcum at 0.2 °C is 0.72 [0.56,0.91] times that of the highest risk. Due to this non-linearity, the shape of the lag response curve necessarily varied by temperature. This work suggests that on a given day, air temperature approximately 15 °C maximises the incidence of COVID-19, with the effects distributed in the subsequent ten days or more.
This study explores the comprehensive effects of green finance (GF) on the low-carbon transition of the energy system (LTES) by analyzing panel data from 281 cities in China from 2006 to 2021. It is found that GF significantly reduces overall energy consumption and exhibits a U-shaped association with energy efficiency, while its relationship with the energy consumption structure is inverted U-shaped. After accounting for endogeneity in the robustness tests, these findings remain consistent and are therefore deemed reliable. A mechanistic analysis reveals that GF promotes industrial upgrading, technological progress, and economic agglomeration, collectively facilitating the LTES. The impact of GF on LTES shows considerable variation among regions, influenced by their levels of economic growth, extents of marketization, and governmental environmental preferences. Our findings provide new evidence for the relationship between GF and LTES, offering a scientific basis for formulating GF policies to accelerate this transformation.
This research explores the issue of local management system governing the heritage preservation in UNESCO World Heritage Site (WHS) Stadthuys, Melaka. Thus far, there is no clearly defined value of cultural heritage that justifies the benefits of preserving cultural heritage as a tourism product and as a sustainable heritage site. Most studies have proven that visitors in general are less interested in visiting cultural heritage sites due to the lack of information available there. Another issue identified in the recent research on cultural heritage assessment is the lack of empirical references on the economic valuation of cultural heritage preservation. This study used contingent valuation method (CVM) and questionnaire for data collection. Four sets of questionnaires were designed and distributed to a total of 100 respondents consisting of local community and domestic tourists. On average, respondents are willing to pay RM8.82, in which this value is higher than the current fee, RM5.00, showing that visitors have the awareness to value cultural heritage through preservation in Stadthuys, Melaka, WHS. Finally, this research has established a framework to be considered by the management regarding the WTP value of the cultural heritage in order to create a more sustainable Melaka Historical City.
Atmospheric Pollution due to airborne particle is a major concern to many cities in the Southeast Asian region, including Kuala Lumpur. Within the last six years air particulate samples have been collected from a site in Kuala Lumpur and measured for their PM10, PM2.5 and elemental concentrations. The results showed that the daily PM10 (
Relationship between understory plant diversity and anthropogenic disturbances in urban forests of Wuhan City, Central China, was analyzed by diversity analysis and detrended canonical correspondence analysis (DCCA). The results showed that: understory species diversity was higher in suburban area than in urban area. From forest center to edge, species diversity of Luojia hill, Shizi hill and Maan hill forests gradually increased, however, that of Hong hill gradually decreased. Anthropogenic disturbances gradient resulted from visitors flowrate, shrub coverage, aspect and adjacent land types had significant effects on species diversity of shrub and herb layers in urban forests. High anthropogenic disturbances might increase similar non-native herb species in urban area and low disturbances might promote co-existence of wood species in suburban area. Further analysis on types of anthropogenic disturbances and plant functional groups in urban-suburban gradient should be taken into a consideration.
Food security is the cornerstone that ensures the stable development of a country. Based on panel data of 31 provinces (including autonomous regions and municipalities) in China from 2015 to 2019, we use the mediating effect model to explore the mechanism by which food consumption structure affects food security. The results indicate that grain consumption has a significant promoting effect on food security, while plant and animal food consumption have significant inhibiting effects on food security. Furthermore, agricultural R&D and investment play mediating roles in the impact of food consumption structure on food security. Obvious differences exist in the relationship between food consumption structure and food security between urban and rural areas, as well as between Eastern, Central, and Western regions. Animal food consumption had a negative and significant impact on food security, with a stronger effect on rural residents than on urban residents. Compared with the central and western regions, grain consumption and animal food consumption in the eastern region had a stronger marginal impact on food security. This paper enriches and expands the research on influencing factors of food security from the perspective of consumer demand, which has important theoretical value and practical significance for ensuring food security.
Urban areas worldwide are in the race to become smarter, and the Kingdom of Saudi Arabia (KSA) is no exception. Many of these have envisaged a chance to establish devoted municipal access networks to assist all kinds of city administration and preserve services needing data connectivity. Organizations unanimously concentrate on sustainability issues with key features of general trends, particularly the combination of the 3Rs (reduce waste, reuse and recycle resources). This paper demonstrates how the incorporation of the Internet of Things (IoT) with data access networks, geographic information systems and combinatorial optimization can contribute to enhancing cities' administration systems. A waste-gathering approach based on supplying smart bins is introduced by using an IoT prototype embedded with sensors, which can read and convey bin volume data over the Internet. However, from another perspective, the population and residents' attitudes directly affect the control of the waste management system. The conventional waste collection system does not cover all areas in the city. It works based on a planned scheme that is implemented by the authorized organization focused on specific popular and formal areas. The conventional system cannot observe a real-time update of the bin status to recognize whether the waste level condition is 'full,' 'not full,' or 'empty.' This paper uses IoT in the container and trucks that secure the overflow and separation of waste. Waste source locations and population density influence the volume of waste generation, especially waste food, as it has the highest amount of waste generation. The open public area and the small space location problems are solved by proposing different truck sizes based on the waste type. Each container is used for one type of waste, such as food, plastic and others, and uses the optimization algorithm to calculate and find the optimal route toward the full waste container. In this work, the situations in KSA are evaluated, and relevant aspects are explored. Issues relating to the sustainability of organic waste management are conceptually analyzed. A genetic-based optimization algorithm for waste collection transportation enhances the performance of waste-gathering truck management. The selected routes based on the volume status and free spaces of the smart bins are the most effective through those obtainable towards the urgent smart bin targets. The proposed system outperforms other systems by reducing the number of locations and smart bins that have to be visited by 46% for all waste types, whereas the conventional and existing systems have to visit all locations every day, resulting in high cost and consumption time.
Sustainable urban development has been a popular subject in urban studies and related disciplines. Owing to the challenges faced by cities worldwide to accommodate the growing urban populations, it is becoming ever more important for innovative research on sustainable urban development to be performed to help cities achieve sustainability. This study develops and tests an integrated approach to sustainable city assessment, which is a combination of importance-performance analysis (IPA) and modified analytic hierarchy process (AHP). Questionnaires designed following the IPA concept were distributed to residents of three cities. The importance scores from the collected data were factorized and the factors' relative scores were then calculated using a formula developed in this study to represent pairwise comparisons. The derived criteria weights were applied to the performance scores to evaluate the cities' relative overall sustainability performance. This approach replaces the AHP's 1-9 scale with the IPA's importance rating scale, which is a Likert scale, in the questionnaire. Based on the findings, implications and future research suggestions were provided.
Dexing City is an important mining city in China, abounding in copper ore, lead ore, zinc ore, and other metal resources, and there are two large open-pit mines in its territory, Dexing Copper Mine and Yinshan Mine. The two open-pit mines have been expanding their mining production scale since 2005, with frequent mining activities; and the expansion of the pits and the discharge of solid waste will undoubtedly increase the land use and cause the destruction of vegetation. Therefore, we plan to visualize the change in vegetation cover in Dexing City from 2005 to 2020 and the expansion of the two open-pit mines by calculating changes of the Fractional Vegetation Cover (FVC) in the mining area using remote sensing technology. In this study, we calculated the FVC of Dexing City in 2005, 2010, 2015 and 2020 using data from NASA Landsat Database via ENVI image analysis software, plotted the FVC reclassified maps via ArcGIS, and conducted field investigations in the mining areas of Dexing City. In this way, we can visualize the spatial and temporal changes of vegetation cover in Dexing City from 2005 to 2020, and appreciate the situation of mining expansion and its solid waste discharge in Dexing City. The results of this study showed that the vegetation cover of Dexing City remained stable from 2005 to 2020, as the expansion of mining scale and mine pits was accompanied by active environmental management and land reclamation, setting a positive example for other mining cities.
In light of the ongoing occurrence of epidemics, the general populace frequently makes the decision to curtail their nomadic lifestyle in order to protect both their health and their safety. This has resulted in a number of issues, the most notable of which are the drop in the people's living happiness index and the poor business that the tourism industry has been experiencing as a result. Therefore, the idea of "cloud tourism" is undoubtedly the first candidate for the tourism industry, and in order to meet the requirements of cloud tourism, it is necessary to have an entirely new system to serve this, of which the scenic guide robot is an important part. At the same time, the quickening development of 5G technology offers solutions that may be put into practice for the multifurther IoT's expansion in smart cities. People will be able to experience the real outdoors without having to leave their homes, which will improve the people's well-being and alleviate the chilly status quo in the tourism industry. This is the plan, and it will be accomplished through the use of innovative guide robots that will make the experience more convenient and reliable.
During 30 years of unprecedented urbanization, plant diversity in Shenzhen, a young megacity in southern China, has increased dramatically. Although strongly associated with plant diversity, butterfly diversity generally declines with urbanization, but this has not been investigated in Shenzhen. Considering the speed of urbanization in Shenzhen and the large number of city parks, we investigated butterfly diversity in Shenzhen parks. We measured butterfly species richness in four microhabitats (groves, hedges, flowerbeds, and unmanaged areas) across 10 parks and examined the relationship with three park variables: park age, park size, and distance from the central business district. Butterflies were identified based on wing morphology and DNA barcoding. We collected 1933 butterflies belonging to 74 species from six families; 20% of the species were considered rare. Butterfly species richness showed weak negative correlations with park age and distance from the central business district, but the positive correlation with park size was statistically significant (p = 0.001). Among microhabitat types, highest species richness was recorded in unmanaged areas. Our findings are consistent with others in suggesting that to promote urban butterfly diversity it is necessary to make parks as large as possible and to set aside areas for limited management. In comparison to neighbouring cities, Shenzhen parks have high butterfly diversity.
This study assesses waste management and recycling practices of the urban poor households residing as squatters and in low-cost flats of Kuala Lumpur city, Malaysia. To attain the objective, the study employed some statistical techniques such as t-tests of equality of means, one-way analysis of variance, chi-squared 'likelihood ratio' tests, and simple descriptive statistics. The statistical techniques were used to determine and analyse the factors that significantly influence the environmental behaviour of the urban poor concerning solid waste management, particularly their recycling practices. The findings of the study show that the urban poor and low-income communities have been proved to behave in ways that are consistent with and conducive to environmentally friendly solid waste management. This study provides evidence that the urban poor and low-income communities are the main recyclers, re-users, and source-reducers of their household solid waste. The study, however, suggests that policies should be formulated to focus on promoting knowledge, education, and the skills of the urban poor and, in addition, to empower them as a means of improving their quality of life.
Inflow and infiltration are important aspects of sewerage systems that need to be considered during the design stage and constantly monitored once the sewerage system is in operation. The aim of this research is to analyse the relationship of rainfall as well as inflow infiltration with sewage flow patterns through data collected from fieldwork. Three sewer pipelines were selected at the residential areas of Taman Lepar Hilir Saujana, Bandar Putra and Kota Sas for data collection. Sewage flow data were collected in terms of flowrate, velocity and depth of flow using flowmeters with ultrasonic sensors that utilize the continuous Doppler effect in the sewer pipelines, while rainfall intensity data were collected using rain gauges installed at the study locations. Based on the result, the average infiltration rates of Qpeak and Qave for the locations were 17% and 21%, which exceeded the respective values of 5% and 10% stated in Hammer and Hammer. The flowrate of wastewater in the sewer pipelines was found to be directly proportional to rainfall. These findings indicate that the sewer pipelines in the study areas may have been affected by capacity reduction, whereas the sewerage treatment plants receiving the wastewater influent may have been overloaded.
Under the new development model, the digital economy has become a new engine to promote the green development of the economy and achieve the goal of "double carbon." Based on panel data from 30 Chinese provinces and cities from 2011 to 2021, the impact of the digital economy on carbon emissions was empirically studied by constructing a panel model and a mediation model. The results show that firstly, the effect of the digital economy on carbon emissions is a non-linear inverted "U" shaped relationship, and this conclusion still holds after a series of robustness tests; secondly, the results of the benchmark regression show that economic agglomeration is an essential mechanism through which the digital economy affects carbon emissions and that the digital economy can indirectly suppress carbon emissions through economic agglomeration. Finally, the results of the heterogeneity analysis show that the impact of the digital economy on carbon emissions varies according to the level of regional development, and its effect on carbon emissions is mainly in the eastern region, while its impact on the central and western regions is weaker, indicating that the impact effect is primarily in developed regions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the development strategy of the digital economy according to local conditions to promote a more significant carbon emission reduction effect of the digital economy.